Intelligent subsystem in a access networks

ABSTRACT

An intelligent subsystem coupled with a radio transceiver, a voice processing module, an intelligent (smart) camera, a first set of computer implementable instructions in an artificial intelligence algorithm and a fuzzy logic algorithm (stored in one or more non-transitory storage medias) and a second set of computer implementable instructions to provide a search on an internet in response to a user&#39;s interest/preference (stored in the one or more non-transitory storage medias), wherein the first set of computer implementable instructions and the second set of computer implementable instructions are combined/integrated or separated.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is

-   -   a continuation-in-part (CIP) patent application of (a) U.S.        Non-Provisional patent application Ser. No. 16/974,218 entitled        “Intelligent Subsystem In Access Networks”, filed on Nov. 16,        2020,    -   wherein (a) is a continuation patent application of (b) U.S.        non-provisional patent application Ser. No. 16/602,095 entitled        “Intelligent Subsystem In Access Networks”, filed on Aug. 5,        2019,    -   wherein (b) is a continuation patent application of (c) U.S.        non-provisional patent application Ser. No. 16/350,132 entitled        “Intelligent Subsystem in Access Networks”, filed on Oct. 2,        2018,    -   wherein (c) is a continuation patent application of (d) U.S.        non-provisional patent application Ser. No. 15/731,313 entitled        “Access Communication System With Object/Intelligent        Appliance-To-Object/Intelligent Appliance Interaction”, filed on        May 23, 2017, (which resulted in a U.S. Pat. No. 10,154,326,        issued on Dec. 11, 2018),    -   wherein (d) is a continuation patent application of (e) U.S.        non-provisional patent application Ser. No. 14/999,984 entitled        “Dynamic Intelligent Bidirectional Optical Access Communication        System With Object/Intelligent Appliance-To-Object/Intelligent        Appliance Interaction”, filed on Jul. 25, 2016, (which resulted        in a U.S. Pat. No. 9,723,388, issued on Aug. 1, 2017),    -   wherein (e) is a continuation patent application of (f) U.S.        non-provisional patent application Ser. No. 14/014,239 entitled        “Dynamic Intelligent Bidirectional Optical Access Communication        System With Object/Intelligent Appliance-To-Object/Intelligent        Appliance Interaction”, filed on Aug. 29, 2013, (which resulted        in a U.S. Pat. No. 9,426,545, issued on Aug. 23, 2016),    -   wherein (f) is a continuation patent application of (g) U.S.        non-provisional patent application Ser. No. 12/931,384 entitled        “Dynamic Intelligent Bidirectional Optical Access Communication        System With Object/Intelligent Appliance-To-Object/Intelligent        Appliance Interaction”, filed on Jan. 31, 2011, (which resulted        in a U.S. Pat. No. 8,548,334, issued on Oct. 1, 2013),    -   wherein (g) claims the benefit of priority to (h) U.S.        provisional application Ser. No. 61/404,504 entitled “Dynamic        Intelligent Bidirectional Optical Access Communication System        With Object/Intelligent Appliance-To-Object/Intelligent        Appliance Interaction”, filed on Oct. 5, 2010,    -   wherein (g) is a continuation-in-part (CIP) of (i) U.S.        non-provisional patent application Ser. No. 12/238,286 entitled        “Portable Internet Appliance”, filed on Sep. 25, 2008, and    -   wherein (i) is a continuation-in-part (CIP) of (j) U.S.        non-provisional patent application Ser. No. 11/952,001, entitled        “Dynamic Intelligent Bidirectional Optical and Wireless Access        Communication System, filed on Dec. 6, 2007, (which resulted in        a U.S. Pat. No. 8,073,331, issued on Dec. 6, 2011),    -   wherein (j) claims the benefit of priority to    -   (k) U.S. provisional patent application Ser. No. 60/970,487        entitled “Intelligent Internet Device”, filed on Sep. 6, 2007,    -   (l) U.S. provisional patent application Ser. No. 60/883,727        entitled “Wavelength Shifted Dynamic Bidirectional System”,        filed on Jan. 5, 2007,    -   (m) U.S. provisional patent application Ser. No. 60/868,838        entitled “Wavelength Shifted Dynamic Bidirectional System”,        filed on Dec. 6, 2006.

The entire contents of all (i) U.S. Non-Provisional patent applications,(ii) U.S. Provisional patent applications, as listed in the previousparagraph and (iii) the filed (patent) Application Data Sheet (ADS) arehereby incorporated by reference, as if they are reproduced herein intheir entirety.

FIELD OF THE INVENTION

Bandwidth demand and total deployment cost (capital cost and operationalcost) of an advanced optical access communication system are increasing,while a return on investment (ROI) is decreasing. This has created asignificant business dilemma.

More than ever before, we have become more mobile and global.Intelligent pervasive and always-on internet access via convergence ofall (e.g., an electrical/optical/radio/electromagnetic/sensor/biosensor)communication networks can provide connectivity at anytime, fromanywhere, to anything is desired.

The present invention is related to a dynamic bidirectional opticalaccess communication system with an intelligent subscriber subsystemthat can connect/couple/interact (via one/more/all the networks aslisted hereinafter:electrical/optical/radio/electromagnetic/sensor/biosensor communicationnetwork(s)) with an object and an intelligent appliance, utilizinginternet protocol version 6 (IPv6) and its subsequent versions.

An intelligent subscriber system and/or an object and/or an intelligentappliance includes one/more of the following: (a) modules (wherein amodule is defined as a functional integration of criticalelectrical/optical/radio/sensor components, circuits and algorithmsneeded to achieve a desired function/property of a module): a laser, aphotodiode, a modulator, a demodulator, a phase-to-intensity converter,an amplifier, a wavelength combiner/decombiner, an optical powercombiner/decombiner, a cyclic arrayed waveguide router, amicro-electrical-mechanical-system (MEMS) space switch, an opticalswitch, an optical circulator, an optical filter, an optical intensityattenuator, a processor, a memory, a display component, a microphone, acamera, a sensor, a biosensor, a radio, a near-field-communication(NFC), a scanner, a power source, (b) an embedded and/or a cloud basedoperating system software module (wherein a software module is definedas a functional integration of critical algorithms needed to achieve adesired function/property of a software module) and/or (c) an embeddedand/or a cloud based intelligence rendering software module.

Furthermore, an object can sense/measure/collect/aggregate/compare/mapand connect/couple/interact (via one/more/all the networks as listedhereinafter: electrical/optical/radio/electromagnetic/sensor/biosensorcommunication network(s)) with another object, an intelligent subscribersubsystem and an intelligent appliance, utilizing internet protocolversion 6 (IPv6) and its subsequent versions.

SUMMARY OF THE INVENTION

A dynamic intelligent bidirectional optical access communication systemutilizes two critical optical modules: a phase modulator and anintensity modulator at an intelligent subscriber subsystem. Together,these two critical optical modules can reduce the Rayleighbackscattering effect on the propagation of optical signals.

The reduced Rayleigh backscattering effect can enable a longer-reachoptical access communication network (longer-reach than a currentlydeployed optical access communication network) between an intelligentsubscriber subsystem and a super node (e.g., many neighboring nodescollapsed into a preferred super node). Such a longer-reach opticalaccess communication network can eliminate significant costs related toa vast array of middle equipment (e.g., a router/switch), whichotherwise would be needed between a standard node (without a super nodeconfiguration) and a large number of remote nodes, according to acurrently deployed optical access communication network.

In one embodiment of the present invention, a bidirectional opticalaccess communication system can be configured to be capable of alonger-reach optical access communication network.

In another embodiment of the present invention, a bidirectional opticalaccess communication system can be configured to be capable ofdynamically providing wavelength on-Demand and/or bandwidth on-Demandand/or service on-Demand.

In another embodiment of the present invention, fabrication andconstruction of a wavelength tunable laser component/module isdescribed.

In another embodiment of the present invention, an optical signal can berouted to an intended destination securely by extracting an intendeddestination from a destination marker optical signal.

In another embodiment of the present invention, fabrication,construction and applications of an object are described.

In another embodiment of the present invention, an object cansense/measure/collect/aggregate/compare/map and connect/couple/interact(via one/more/all the networks as listed hereinafter:electrical/optical/radio/electromagnetic/sensor/biosensor communicationnetwork(s)) with another object, an intelligent subscriber subsystem andan intelligent appliance, utilizing internet protocol version 6 (IPv6)and its subsequent versions.

In another embodiment of the present invention, an intelligencerendering software module allows a subscriber subsystem toadapt/learn/relearn a user's interests/preferences/patterns, therebyrendering intelligence to a subscriber subsystem.

In another embodiment of the present invention, an intelligencerendering software module allows an appliance to adapt/learn/relearn auser's interests/preferences/patterns, thereby rendering intelligence toan appliance.

In another embodiment of the present invention, fabrication andconstruction of a near-field communication enabledmicro-subsystem/intelligent appliance is described.

In another embodiment of the present invention, a portfolio ofapplications (e.g., an intelligent, location based and personalizedsocial network and direct/peer-to-peer marketing) is also described.

The present invention can be better understood in the description belowwith accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram configuration of a bidirectionaloptical access communication network 100, according to one embodiment ofthe present invention.

FIG. 2 illustrates a block diagram configuration of a dynamicbidirectional optical access communication network 100, according toanother embodiment of the present invention.

FIG. 3 illustrates a block diagram fabrication and construction of anoptical processing micro-subsystem 360 (within an intelligent subscribersubsystem), according to another embodiment of the present invention.

FIG. 3A illustrates a block diagram fabrication and construction of awavelength tunable (narrowly) laser component, according to anotherembodiment of the present invention.

FIG. 3B illustrates a block diagram fabrication and construction of awavelength tunable (widely) laser array module, according to anotherembodiment of the present invention.

FIG. 4 illustrates a block diagram fabrication and construction of anintelligent subscriber subsystem 340, according to another embodiment ofthe present invention.

FIG. 5 illustrates a block diagram fabrication and construction of anobject 720, according to another embodiment of the present invention.

FIG. 6 illustrates a block diagram fabrication and construction of anintelligent appliance 880, according to another embodiment of thepresent invention.

FIG. 7 illustrates a method flow-chart of an intelligent, location basedand personalized social network, according to another embodiment of thepresent invention.

FIG. 8 illustrates a method flow-chart of intelligent, location basedand personalized direct marketing, according to another embodiment ofthe present invention.

FIG. 9 illustrates a method flow-chart of intelligent, location basedand personalized secure contactless (proximity) internet accessauthentication, according to another embodiment of the presentinvention.

FIG. 10 illustrates connections/couplings/interactions between theobject 720 (including with another object 720), the intelligentsubscriber subsystem 340 and the intelligent appliance 880, according toanother embodiment of the present invention.

FIG. 11 illustrates a method flow-chart enabling task execution by asoftware agent, according to another embodiment of the presentinvention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 illustrates a block diagram configuration of a bidirectionaloptical access communication network 100, which includes a super node101, many distant local nodes 102 and many distant remote nodes 103. Thedistance between the super node 101 and the remote node 103 is greaterthan the distance between the super node 101 and the local node 102.However, many local nodes 102 can collapse/reside within the super node101 to enable a bidirectional optical access communication network 100,without a roadside electrical power requirement at the local node 102.

A bidirectional optical access communication network 100 isconnected/coupled/interacted with the super node 101, many local nodes102, many remote nodes 103 and a large number of intelligent subscribersubsystems 340 s (located at homes/businesses) over adispersion-compensated single-mode optical fiber 280. At the super node101, a number of laser modules (high power fast wavelengthswitching-wavelength tunable semiconductor laser modules are preferred)120 s provide a first set of downstream wavelengths, where eachdownstream wavelength is modulated at 10 Gb/s or higher Gb/s, by acorresponding intensity modulator module (anelectro-absorption/Mach-Zehnder intensity modulator module is preferred)140 to provide optical signals. These modulated downstream wavelengths(embedded with the optical signals) are combined by a wavelengthcombiner module 160 and amplified by an erbium-doped fiber amplifier(EDFA) module 220. These amplified downstream wavelengths are passedthrough a 3-port circulator module 260 and transmitted over thedispersion-compensated single-mode optical fiber (with a distributedRaman amplifier is preferred) 280 to the remote node 103. A distributedRaman amplifier can provide distributed amplification of the opticalsignal over the dispersion-compensated single-mode optical fiber 280 bynonlinear coupling/interaction between the optical signal and an opticalpump signal, thereby effectively increasing the reach of an opticalaccess communication network more than a currently deployed opticalaccess communication network. At the remote node 103, the modulateddownstream wavelengths from the super node 101, are decombined by anintegrated wavelength combiner/decombiner module 300, filtered by abandpass optical filter module (a wavelength switching-wavelengthtunable bandpass optical filter module is preferred) 240, are powersplit by an integrated optical power combiner/decombiner module 320 andare transmitted to a number of intelligent subscriber subsystems 340 s.However, all the optical modules at the remote node 103 must betemperature insensitive to operate within a wide temperature range atthe remote node 103, as there may not be an option of an electricalpower at the remote node 103. The downstream wavelengths from the supernode 101 to the number of intelligent subscriber subsystems 340 s can betransmitted and correspondingly received by photodiode modules 200 s atthe intelligent subscriber subsystems 340 s, utilizing a time divisionmultiplexed statistical bandwidth allocation and/or a broadcastingmethod.

The local node 102 includes the laser module 120, which isconnected/coupled/interacted with the erbium-doped fiber amplifier(EDFA) module 220 to provide an upstream wavelength from the intelligentsubscriber subsystems 340 s, which is offset in wavelength with respectto the first set of downstream wavelengths generated at the super node101. The upstream wavelength power splits through the integrated opticalpower combiner/decombiner module 320 at the remote node 103 and istransmitted to the number of intelligent subscriber subsystems 340 s forfurther optical processing by an optical processing micro-subsystem 360.An optically processed upstream wavelength (embedded with the opticalsignals) by the optical processing micro-subsystem 360 (within theintelligent subscriber subsystem 340) is looped/returned back throughthe integrated optical power combiner/decombiner module 320, thebandpass optical filter module 240 and the integrated wavelengthcombiner/decombiner module 300 at the remote node 103. The opticallyprocessed upstream wavelength is transmitted over thedispersion-compensated single-mode optical fiber 280 and passed throughthe 3-port circulator module 260 at the super node 101. The 3-portcirculator module 260 provides the upstream wavelengths from a number ofintelligent subscriber subsystems 340 s to the bandpass optical filter240, the erbium-doped fiber amplifier (EDFA) module 220, the wavelengthdecombiner module 180, a number of external fiber-optic interferometermodules 180As (to convert a phase modulation signal into an intensitymodulation signal) and the photodiode modules 200 s at the super node101, wherein each photodiode module 200 is detecting the distinctupstream wavelength. Furthermore, each photodiode module 200 includesone or more of the following optical/electronic components: a 10 Gb/s orhigher Gb/s linear photodiode chip, a 10 Gb/s or higher Gb/smesa-type/waveguide-type avalanche photodiode chip (APD), a 10 Gb/s orhigher Gb/s burst-mode transimpedance amplifier, a 10 Gb/s or higherGb/s clock and data recovery (CDR), the bandpass optical filter 240 anda semiconductor optical amplifier 380 (if the semiconductor opticalamplifier 380 is needed for optical gain in conjunction with a 10 Gb/sor higher Gb/s linear photodiode chip). The upstream wavelength from anumber of intelligent subscriber subsystems 340 s to the super node 101can be transmitted and correspondingly received by the photodiodemodules 200 s at the super node 101, utilizing a time divisionmultiplexed statistical bandwidth allocation and/or a broadcastingmethod.

FIG. 2 illustrates a block diagram configuration of a dynamicbidirectional optical access communication network 100, where anywavelength to the intelligent subscriber subsystem 340 can bedynamically varied on-Demand by utilizing an M:M cyclic wavelengtharrayed waveguide grating router module (a fast wavelengthswitching-wavelength tunable programmable M:M cyclic wavelength arrayedwaveguide grating router module is preferred) 250 at the remote node103. All possible switched output downstream wavelengths are arranged atthe M outputs of the M:M cyclic wavelength arrayed waveguide gratingrouter module 250 because of the free spectral range periodic propertyof the M:M cyclic wavelength arrayed waveguide grating router module.This configuration offers the flexibility of dynamicallyrouting/delivering one or more downstream wavelengths with differentmodulation rates (e.g., 10 Gb/s or higher Gb/s) provided by thecorresponding intensity modulator module 140, to the intelligentsubscriber subsystem 340 for wavelength on-Demand, bandwidth on-Demandand service on-Demand, significantly increasing a return on investment.Thus, each dynamically routed wavelength with a specific modulation ratecan provide a distinct bandwidth-specific service on-Demand (e.g., anultra-high definition movie on-Demand) to the specific intelligentsubscriber subsystem 340.

A method of providing bandwidth-specific service on-Demand can berealized by including at least the steps: (a) the user requesting aspecific service (e.g., an ultra-high definition movie on-Demand) at thespecific intelligent subscriber subsystem 340, (b) delivering thespecific service over a wavelength by the laser module 120 from thesuper node 101, (c) modulating the wavelength at a required modulationrate (e.g., 10 Gb/s or higher Gb/s) by the intensity modulator module140 at the super node 101 and (d) then dynamically routing the saidwavelength (embedded with the user requested specific service) by theM:M cyclic wavelength arrayed waveguide grating router module 250 at theremote node 103 and to the specific intelligent subscriber subsystem340.

Furthermore, rapid wavelength routing (in space, wavelength and time) bythe M:M cyclic wavelength arrayed waveguide grating router module 250can be fabricated/constructed as an optical packet/interconnect routerbetween many printed circuit boards/integrated circuits/processors.

Additionally, outputs of the M:M cyclic wavelength arrayed waveguidegrating router module 250 at the remote node 103 can beconnected/coupled/interacted with inputs of a large-scale N:N (e.g., a1000:1000) micro-electrical-mechanical-system space switch module at theremote node 103 to provide much greater flexibility of wavelengthrouting.

An input-output echelle grating module and/or a negative-index photoniccrystal super-prism module can be utilized as alternatives to thewavelength combiner module 160, the wavelength decombiner module 180 andthe integrated wavelength combiner/decombiner module 300. A multi-modeinterference (MMI) module and/or a Y-combiner module can be utilized asalternatives to the integrated optical power combiner/decombiner module320 and the optical power combiner module 320A.

FIG. 3 illustrates a block diagram construction of the opticalprocessing micro-subsystem 360, wherein a downstream wavelength ispassed through the 3-port circulator 260, the bandpass optical filtermodule 240 and the photodiode module 200. A wavelength from the lasermodule 120 at the local node 102 is passed through the 3-port circulatormodule 260 within the optical processing micro-subsystem 360 and thiswavelength is amplified by the semiconductor optical amplifier module380, modulated in phase by a phase modulator module 400, modulated at abit-rate (e.g., 10 Gb/s or higher Gb/s, but a variable modulationbit-rate is preferred) in intensity by an intensity modulator module420, amplified by the semiconductor optical amplifier module 380,transmitted through a variable optical intensity attenuator module 440(if needed) and looped/returned back to create the upstream wavelength(embedded with an optical signal from the intelligent subscribersubsystem 340) and transmitted to the super node 101.

Furthermore, the generic intensity modulator module 140 can be replacedby an electro-absorption intensity modulator module 420, which isdesigned for integration with the semiconductor optical amplifier module380, the phase modulator module 400 and the variable optical intensityattenuator module 440 on a monolithic photonic integrated circuit (PIC)and/or an active-passive hybrid planar lightwave circuit (PLC)technology.

Numerous permutations (e.g., modulating a CW optical signal from thelaser module 120 at the local node 102 by the intensity modulator140/420 and then by the phase modulator 400) of all optical moduleswithin the optical processing micro-subsystem 360 are possible to createoptimum quality of the upstream wavelength for an intended reach. Use ofthe phase modulator module 400 and the intensity modulator module 420together can reduce the Rayleigh backscattering effect on thepropagation of optical signals, enabling a longer-reach optical accesscommunication network between the super node 101 and the remote node103, thus eliminating a vast array of middle equipment such as routersand switches, which would otherwise be needed between a standard node(without the super node configuration) and a large number of the remotenodes 103 s, according to a currently deployed optical accesscommunication network.

According to another embodiment of the present invention, an upstreamsecond set of wavelengths (which are offset in wavelengths with respectto the first set of wavelengths transmitted from the super node 101) canbe internally generated by a wavelength tunable laser module within theintelligent subscriber subsystem 340, without the need for externalwavelength generation by the laser module 120 at the local node 102.Generation of the upstream wavelength (fast switching-widely tunablelaser module is preferred) within the intelligent subscriber subsystem340 simplifies fabrication and construction of a dynamic bidirectionaloptical access communication network 100.

According to another embodiment of the present invention, asingle-mode/mode-hopp free wavelength tunable (about 32 nm) laser modulecan be constructed by utilizing an ultra-low anti-reflection coated(both facets) semiconductor optical amplifier (a quantum dotsemiconductor optical amplifier is preferred) and a triple-ringresonator waveguide on a planar lightwave circuit platform. The frontfacet of the triple-ring resonator waveguide has an ultra-lowanti-reflection coating, while the back facet of that has ahigh-reflection coating. The anti-reflection coated back facet of thesemiconductor optical amplifier and the anti-reflection coated frontfacet of the triple-ring resonator waveguide are intimately attached(“butt-coupled”) to each other. The phases of a triple-ring resonatorwaveguide can be controlled by a metal strip heater along a straightsegment of the triple-ring resonator waveguide. Furthermore, thesemiconductor optical amplifier 380 can be monolithically integratedwith the electro-absorption (EAM)/Mach-Zehnder intensity modulator.

FIG. 3A illustrates a block diagram fabrication and construction of asingle-mode/mode-hopp free wavelength tunable (narrow) laser component,including an electro-absorption modulator segment 400 (about 150 micronslong), which can be integrated (“butt-coupled”) with the back facet of aλ/4 phase shifted DR laser (λ/4 phase shifted distributed feedback (DFB)section (about 400 microns long)+phase control section (without anygratings/about 50 microns long)+distributed Bragg reflector (DBR)section (about 50 microns long)) 120A. Laser multi-quantum-well (MQW)layers can be stacked on top of electro-absorption intensity modulatormulti-quantum-well layers. An electro-absorption intensity modulator canbe processed by etching away the laser multi-quantum-well layers. Higherlaser output (exit power) can be achieved by incorporating distributedphase shifts and/or chirped grating across the length of a distributedfeedback section. An injection current to a phase control section canproduce a change in distributed feedback laser wavelength.Reverse-voltage to the electro-absorption intensity modulator 420 canchange in a refractive index by Quantum Confined Stark Effect (QCSE).The advantages of this tunable laser design are (1) high single-modestability due to a distributed feedback section, (2) higher output(exit) power due to a distributed Bragg reflector section and (3) rapidwavelength tuning by an injection current to a phase control sectionand/or reverse voltage to the electro-absorption intensity modulator420.

A stacked multi-quantum well cross-sectional layer design of theelectro-absorption modulator with the DR laser is illustrated in Table Ibelow.

TABLE 1 N—/P— Composition Bandgap Thickness Doping In(1-x)Ga(x)Wavelength Strain Material (nm) (10{circumflex over ( )}18/cm{circumflexover ( )}3) As(y)P(1-y) (nm) (%) Index Substrate 100 × 10{circumflexover ( )}3 N 3.0 X = 0.000 918.6 0 3.1694 Y = 0.000 Buffer  1 ×10{circumflex over ( )}3 N 1.0 X = 0.000 918.6 0 3.1694 Y = 0.000 1.15Q70 N 0.5 X = 0.181 1150 0 3.3069 Y = 0.395 1.20Q 50 N 0.5 X = 0.216 12000 3.3345 Y = 0.469 1.10Q 10 N 0.001 X = 0.145 1100 0 3.2784 Y = 0.317EAM Well-1 8 N 0.001 X = 0.463 1550 TS0.2 3.5533 Y = 0.930 1.10Q 6 N0.001 X = 0.145 1100 0 3.2784 Y = 0.317 EAM Well-2 8 N 0.001 X = 0.4631550 TS0.2 3.5533 Y = 0.930 1.10Q 6 N 0.001 X = 0.145 1100 0 3.2784 Y =0.317 EAM Well-3 8 N 0.001 X = 0.463 1550 TS0.2 3.5533 Y = 0.930 1.10Q 6N 0.001 X = 0.145 1100 0 3.2784 Y = 0.317 EAM Well-4 8 N 0.001 X = 0.4631550 TS0.2 3.5533 Y = 0.930 1.10Q 6 N 0.001 X = 0.145 1100 0 3.2784 Y =0.317 EAM Well-5 8 N 0.001 X = 0.463 1550 TS0.2 3.5533 Y = 0.930 1.10Q 6N 0.001 X = 0.145 1100 0 3.2784 Y = 0.317 EAM Well-6 8 N 0.001 X = 0.4631550 TS0.2 3.5533 Y = 0.930 1.10Q 10 N 0.001 X = 0.145 1100 0 3.2784 Y =0.317 Stop-Etch 50 N 0.001 X = 0.000 918.6 0 3.1694 Y = 0.000 *1.25Q 10N 0.001 X = 0.239 1250 0 3.3588 Y = 0.533 *DR Well-1 5 N 0.001 X = 0.2391642 CS1.05 3.4971 Y = 0.839 *1.25Q 10 N 0.001 X = 0.239 1250 0 3.3588 Y= 0.533 *DR Well-2 6 N 0.001 X = 0.239 1642 CS1.05 3.4971 Y = 0.839*1.25Q 10 N 0.001 X = 0.239 1250 0 3.3588 Y = 0.533 *DR Well-3 5 N 0.001X = 0.239 1642 CS1.05 3.4971 Y = 0.839 *1.25Q 10 N 0.001 X = 0.239 12500 3.3588 Y = 0.533 *DR Well-4 6 N 0.001 X = 0.239 1642 CS1.05 3.4971 Y =0.839 *1.25Q 10 N 0.001 X = 0.239 1250 0 3.3588 Y = 0.533 *1.20Q 50 P0.2 X = 0.216 1200 0 3.3345 Y = 0.469 **Grating: 50 P 0.2 X = 0.181 11500 3.3069 1.15Q Y = 0.395 Cladding  1.5 × 10{circumflex over ( )}3 P0.2~P2.0 X = 0.000 918.6 0 3.1694 Y = 0.000 1.30Q 50 P 5.0 X = 0.2801300 0 3.3871 Y = 0.606 Cap 200 P 30 X = 0.468 1654 0 3.5610 Y = 1.000EAM: Electro-absorption modulator DR: Laser TS: Tensile CS: Compressive*These laser layers must be removed in EAM section and bereplaced/re-grown with InP layer of total thickness of~172 nm. **λ/4phase shifted gratings (at the DFB section of DR laser) are fabricatedon this layer with 50% duty cycle at 40 nm grating etch depth.

FIG. 3B illustrates a block diagram fabrication and construction of asingle-mode/mode-hopp free wavelength tunable (widely) laser array,which can be integrated with the wavelength combiner 160 or theY/multi-mode interference optical power combiner 320A, the tilted/curvedsemiconductor optical amplifier 380, the phase modulator 400 (ifneeded), the intensity modulator 140/420 and the tilted/curvedsemiconductor optical amplifier 380 via a waveguide 280A/single-modefiber 280. The back facet of the electro-absorption modulator segment400 has a low anti-reflection coating, while the front facet of the lastoptical amplifier 380 has an ultra-low anti-reflection coating. Theupstream wavelength (embedded with an optical signal) generatedutilizing the tunable laser module at the intelligent subscribersubsystem 340, is passed through the 3-port circulator module 260 at theremote node 103 and transmitted to the super node 101. The downstreamwavelength from the super node 101, is passed through the 3-portcirculator 260, the bandpass optical filter module 240 and thephotodiode module 200 at the remote node.

According to another embodiment of the present invention, a subset of asecond set of wavelengths (which are offset in wavelengths with respectto a first set of wavelengths transmitted from the super node 101) canbe modulated at a bit-rate (e.g., 10 Gb/s or higher Gb/s, but a variablemodulation bit-rate is preferred) and thus configured to be shared witha number of intelligent subscriber subsystems 340 s to generate asymmetric upstream bandwidth/bandwidth on-Demand.

Both downstream and upstream wavelengths can be protected by a 2×2optical protection switch module and separated via an opticalring-network including redundant/multiple dispersion-compensatedsingle-mode optical fibers 280 s.

A pilot tone modulation can be added to the semiconductor opticalamplifier module 380 within the optical processing micro-subsystem 360(within the intelligent subscriber subsystem 340) and to the lasermodules 120 s (at the super node 101 and the local node 102) to reducethe Rayleigh backscattering effect.

An electronic dispersion compensation circuit and a forward errorcorrection circuit can be added to relax the specifications of theoptical and/or electronic modules. Furthermore, all optical single-modefibers can be polished at an angle (about 7 degree) to reduce anyoptical back-reflection.

According to another embodiment of the present invention, an upstreamwavelength may be shared/transmitted by a number of the intelligentsubscriber subsystems 340 s, utilizing a time division multiplexedstatistical bandwidth allocation method. Therefore, a burst modereceiver circuit is needed at the super node 101 to process burstyoptical signals embedded in the upstream wavelengths from a number ofthe intelligent subscriber subsystems 340 s.

Furthermore, to enable higher bit-rate, a modulator/demodulator of anadvanced modulation format (e.g., differential quadratic phase-shiftkeying-DQPSK and/or quadratic amplitude modulation-QAM) can be utilized.

FIG. 4 illustrates a block diagram fabrication and construction of theintelligent subscriber subsystem 340, according to another embodiment ofthe present invention, wherein the intelligent subscriber subsystem 340includes the optical processing micro-subsystem 360 (for separating andproviding the downstream wavelength to the photodiode module 200 andoptically processing the upstream wavelength to the super node 101). Thephotodiode module 200 within the optical processing micro-subsystem 360is connected/coupled/interacted with an optical-to-electrical amplifiercircuit 460 and a media access controller (with processing, routing andquality of service (QoS) functions) module and module specific software480. The media access controller module and module specific software 480are connected/coupled/interacted with one or more of the following: (a)an IP/micro IP/light weight IP address module and module specificsoftware 500, (b) a security module (an internetfirewall/spyware/user-specific security control/authentication) andmodule specific software 520, (c) an in-situ/remote diagnostic moduleand module specific software 540, (d) a content transfer module andmodule specific software 560, (e) a time-shift (time-shift is arecording of content to a storage medium for consuming at a later time)module and module specific software 580, (f) a place-shift (place-shiftis consuming stored content on a remoteappliance/subsystem/system/terminal via the internet) module and modulespecific software 600, (g) a content (voice-video-multimedia-data)over-IP module and module specific software 620, (h) a radio module(with antenna(s)), wherein the radio module includes one or more of thefollowing modules: RFID (active/passive), Wibree, Bluetooth, Wi-Fi,Zigbee (Zigbee is an IEEE 802.15.4-based specification), ultra-wideband,60-GHz/millimeter wave, Wi-Max/4G/higher frequency radio and anindoor/outdoor position module (e.g., Bluetooth, Wi-Fi, GPS and anelectronic compass) and module specific software 640, (i) a softwaremodule 700, which includes one or more of the following: embedded/cloudbased operating system software and embedded/cloud based intelligencerendering software (e.g., surveillance software, behavior modeling(e.g., www.choicestream.com), predictive analytics/text/data/patternmining/natural language algorithm (e.g., www.sas.com), a fuzzylogic/artificial intelligence/neural network algorithm (e.g.,www.nd.com/bliasoft.com), machine learning/iterativelearn-by-doing/natural learning algorithm (e.g., www.saffron.com) and anintelligent agent (e.g., www.cougaarsoftware.com)), (j) a memory/storagemodule and module specific software 780, (k) a sensor module and modulespecific software 820 and (l) a battery/solar cell/micro fuel-cell/wiredpower supply module and module specific software 840.

Furthermore, a System-on-a-Chip (SoC), integrating a processor moduleand module specific software 760 with a graphic processor module, aninternet firewall, spyware and the user-specific securitycontrol/authentication can simplify fabrication and construction of theintelligent subscriber subsystem 340.

The intelligent subscriber subsystem 340 includes a set top box/personalvideo recorder/personal server component/module. The intelligentsubscriber subsystem 340 includes a voice-to-text-to-voice processingmodule and module specific software. (e.g., Crisp Sound is real-timeaudio signal processing software for echo cancellation, background noisereduction, speech enhancement and equalization), a video compressionmodule and module specific software, a photo-editing software module anda software module for automatically uploading content to a preferredremote/cloud server.

The intelligent subscriber subsystem 340 has multiple radio modules withmultiple antennas. A tunable radio-frequency carbon nanotube (CNT)cavity can tune in between 2 GHz and 3 GHz. The merger of many antennas,utilizing a tunable carbon nanotube cavity and an analog/digitalconverter can enable a simplified software-defined radio.

The intelligent subscriber subsystem 340 can enable content over-IP,(e.g., Skype service) thus disrupting a traditional carrier controlledfixed telephony business model.

According to another embodiment of the present invention, the securedelivery of a content optical signal to an intended destination can beachieved by utilizing a low bit-rate destination marker optical signal,which is modulated at a different plane with a different modulationformat, simultaneously in conjunction with a higher-bit rate contentoptical signal. The low bit-rate destination marker optical signal isextracted and converted from an optical domain to an electrical domainto determine the intended destination of the content optical signal,while the content optical signal remains in an optical domain until itis delivered to the intended destination—thus both routing and securityin the delivery of the content optical signal can be significantlyenhanced.

FIG. 5 illustrates a block diagram fabrication and construction of amicrosized (about 15 mm³) object 720, having a processor (e.g.,ultra-lower power consumption ARMCortex™-M3/microcontroller-www.ambiqmicro.com/based on nanoscaled InAsXOI) module and module specific software 760 that isconnected/coupled/interacted with one or more of the following: (a) anIP/micro IP/light weight IP address module and module specific software500, (b) a software module 700 (e.g., a Tiny OS-operating system/IBMmote runner), (c) an “object specific” radio module with antenna(s)(which includes one or more of the following: RFID (active/passive), anultra-low power radio, Wibree, Bluetooth and near-field communication740, (d) a memory/storage module and module specific software 780, (e) acamera module (a micro-electrical-mechanical-system based camera ispreferred) and module specific software 800, (f) a sensor (e.g., a radioenabled micro-electro-mechanical sensor) module and module specificsoftware 820 and (g) a battery/solar cell/micro fuel-cell wired powersupply/wired power supply module and module specific software 840. Forexample, a microsized object 720 can also be realized utilizing either aconductive paint or spray-on sensor(s) on a wall. Such a wall can be aninteractive surface and it may sense human touch, human gestures andinteract with other sensors at a home/office.

A battery/solar cell (e.g., silicon)/micro fuel-cell/wired powersupply/resonant electromagnetic inductive coupling energy transfer(wireless) power supply module and module specific software 840 caninclude a thick/thin film (e.g., 3.6V-12 μAh Cymbet thin-film lithiumbattery) printed/three-dimensional/nano-engineered battery (e.g.,cellulose-a spacer ionic liquid electrolyte, electricallyconnected/coupled/interacted with a carbon nanotube electrode and alithium oxide electrode), a nano supercapacitor (e.g., utilizing carbonnanotube ink or operating due to fast ion transport at a nanoscale), anano-electrical generator of piezoelectric PZT nanowires (e.g., 20,000n-/p-type zinc oxide nanowires can generate about 2 mW), anano-electro-mechanical systems (NEMS) cell (e.g., a motor protein cell)and a microbial nano fuel-cell.

A motor protein (macromolecule) named prestin, which is expressed inouter hair cells in the organ of Corti of a human ear and is encoded bythe SLC26A5 gene. Prestin converts an electrical voltage into a motionby elongating and contracting outer hair cells. This motion amplifiessound in a human ear. However, prestin can work in a reverse mode,producing an electrical voltage in response to a motion. To increaseconductivity, a microbe (e.g., a bacterium Pili) can act as a conductingnanowire to transfer electrons generated by prestin. Each prestin cellis capable of making only nano watts of electricity. A prestin cell(array of prestins connected/coupled/interacted between two electrodes)can electrically charge a battery/micro fuel-cell/wired power supplymodule. A prestin cell can grow and self-heal, as it is constructed frombiological components. Furthermore, a nano-electrical generator ofpiezoelectric PZT nanowires can be integrated with prestin.

A memristor component can replace both the processor component and/orthe memory/storage component. Furthermore, a memristor component and anano-sized radio component can reduce power consumption of the object720.

A sensor module and module specific software 820 can include a biosensor(e.g., to monitor/measure body temperature, % oxygen, heart rhythm,blood glucose concentration and a biomarker for a disease parameter).

The object 720 with a biosensor, a transistor, a light emitting diode, anano-sized radio, a prestin cell (for electrical power) and an objectspecific software can be incorporated onto a support material (e.g., asilk membrane) to monitor/measure (and transmit) a disease parameter.

Another example of a biosensor sensor can be an assassin protein(macromolecule) perforin, the immune system's weapon of massdestruction. Perforin is encoded by the PRF1 gene. Perforin is expressedin T cells and natural killer (NK) cells. Interestingly, perforinresembles a cellular weapon employed by a bacterium (e.g., anthrax).Perforin has an ability to embed itself to form a pore in a cellmembrane. The pore by itself may be damaging to a cell and it enablesthe entry of a toxic enzyme granzyme B, which induces apoptosis (aprogrammed suicide process) of a diseased cell. However, perforinoccasionally misfires—killing the wrong cell (e.g., an insulin producingpancreas) and significantly accelerating a disease like diabetes.Defective perforin leads to an upsurge in cancer malignancy (e.g.,leukemia). Up regulation of perforin can be effective against cancerand/or an acute viral disease (e.g., cerebral malaria). Down regulationof perforin can be effective against diabetes. The ramification of apore-forming macromolecule like perforin is enormous, if it can betailored/tuned to a specific disease.

Like perforin, ultrasonically-guided microbubbles can break into a cellmembrane. A pore-forming microbubble (ultrasonically guided)/nanovessel(e.g., a cubisome/liposome) encapsulating a suitablechemical(s)/drug(s), a surface modified red fluorescent protein (e.g.,E2-Crimson) and perforin (if needed) can be an effective imaging/drugdelivery method. A surface coating (e.g., a pegylation) on themicrobubble/nano vessel can avoid the immune surveillance of a humanbody. A surface coating of disease-specific ligand (e.g., an antibody)on a microbubble/nano-vessel can enhance the targeting to specificdisease cells. Furthermore, an encapsulation of magneticsuper-paramagnetic nano-particles within a microbubble/nano-vessel cansignificantly enhance the targeting to onto specific disease cells, whenit is guided by a magnet. The microbubbles/nano-vessels can beincorporated within a silicone micro catheter (coated with silvernanoparticles) tube or a micro-electrical-mechanical-systemreservoir/micropump (integrated with an array of silicon microneedles)on a support material.

For utilizing the object 720 within and/or on a human body, allcomponents must be biocompatible (bio dissolvable is preferred).

If a disease parameter measurement is perceived to be abnormal withrespect to a reference disease parameter measurement, a biosensor moduleconnects/couples/interacts with the object 720 for a programmed drugdelivery. Furthermore, the object 720 can connect/couple/interact (viaone/more/all the networks as listed hereinafter:electrical/optical/radio/electromagnetic/sensor/biosensor communicationnetwork(s)) with another object 720, the intelligent subscribersubsystem 340 and/or an intelligent appliance 880 for locationbased/assisted emergency help without human input.

The object 720 can be fabricated and constructed, utilizing aSystem-on-a-Chip/System-in-a-Package (SiP)/multi-chip module.

The object 720 can sense/measure/collect/aggregate/compare/map andconnect/couple/interact/share (via one/more/all the networks as listedhereinafter: electrical/optical/radio/electromagnetic/sensor/biosensorcommunication network(s)) with another object 720), the intelligentsubscriber subsystem 340 and the intelligent appliance 880, utilizinginternet protocol version 6 (IPv6) and its subsequent versions.

A method of securing information by the object 720, includes at leastthe following steps: (a) sensing 900, (b) measuring 920, (c) collecting940, (d) aggregating/comparing/mapping 960, (e)connecting/coupling/interacting/sharing 980 (in real-time) with theplurality of objects 720 s, intelligent subscriber subsystems 340 s andintelligent appliances 880 s, (f) developing a learning algorithm (e.g.,a machine learning/iterative learn-by-doing/natural learning algorithmin a software module 700) 1300 from the activities of the plurality ofobjects 720 s, intelligent subscriber subsystems 340 s and intelligentappliances 880 s, (g) utilizing a learning algorithm 1320 and (h)re-iterating all the previous steps from (a) to (g) in a loop cycle 1340to enable intelligent decision based on information from the pluralityof objects 720 s, the intelligent subscriber subsystems 340 s and theintelligent appliances 880 s.

FIG. 6 illustrates a block diagram fabrication and construction of theintelligent appliance (about 125 mm long, 75 mm wide and 20 mm thick)880, according to another embodiment of the present invention. Aprocessor (performance at a lower electrical power consumption isdesired e.g., graphene based processor) module and module specificsoftware 760 are connected/coupled/interacted (via one/more/all thenetworks as listed hereinafter:electrical/optical/radio/electromagnetic/sensor/biosensor communicationnetwork(s) with another intelligent appliance) with one or more of thefollowing: (a) an IP/micro IP/light weight IP address module and modulespecific software 500, (b) a security module (an internetfirewall/spyware/user-specific security control/authentication) andmodule specific software 520, (c) an in-situ/remote diagnostic moduleand module specific software 540, (d) a content transfer module andmodule specific software 560, (e) a time-shift module and modulespecific software 580, (f) a place-shift module and module specificsoftware 600, (g) a content (voice-video-multimedia-data) over-IP moduleand module specific software 620, (h) a radio module (with antenna(s)),wherein the radio module includes one or more of the following modules:RFID (active/passive), Wibree, Bluetooth, Wi-Fi, ultra-wideband,60-GHz/millimeter wave, Wi-Max/4G/higher frequency radio and anindoor/outdoor position module (e.g., Bluetooth, Wi-Fi, GPS and anelectronic compass) and module specific software 640, (i) anone-dimensional/two-dimensional barcode/quick response (QR) codescanner/reader module and module specific software 660, (j) a near-fieldcommunication module (with an antenna) and module specific software 680,(k) a software module 700, which includes one or more of the following:embedded/cloud based operating system software and embedded/cloud basedintelligence rendering software (e.g., surveillance software, behaviormodeling (e.g., www.choicestream.com), predictiveanalytics/text/data/pattern mining/natural language algorithm (e.g.,www.sas.com), a fuzzy logic/artificial intelligence/neural networkalgorithm (e.g., www.nd.com/bliasoft.com), machine learning/iterativelearn-by-doing/natural learning algorithm (e.g., www.saffron.com) and anintelligent agent (e.g., www.cougaarsoftware.com)), (l) a memory/storagemodule and module specific software 780, (m) a camera (a 180degree-angle rotating camera module is preferred) and module specificsoftware 800, (n) a sensor module and module specific software 820, (o)a battery (e.g., graphene material based battery)/solar cell/microfuel-cell/wired power supply module and module specific software 840 and(p) a display (a foldable/stretchable display with a touch sensor or aphotonic crystal or a holographic display is preferred) module andmodule specific software 860. An intelligent appliance 880 includes asocket (e.g., SIM/SD).

Furthermore, a camera can include a tunable focal length liquid lens. Asealed transparent (to an optical/viewing axis) optical cell can containtwo immiscible (e.g., water and oil) liquids, having equal physical (notoptical) densities. A pair of piezoelectric sensors/motors can bemechanically coupled (perpendicular to the optical/viewing axis) withthe sealed transparent (optical cell). By applying voltage inputs toeach piezoelectric sensor/motor, mechanically coupled with the sealedtransparent (optical cell), the geometrical shape of one of theimmiscible liquids can be changed rapidly—making a variable/tunablefocal length (liquid) lens. In stead of a pair of piezoelectricsensors/motors, a pair of vanadium dioxide based piezoelectricsensors/motors can be used. Vanadium dioxide is an insulator at a roomtemperature, but abruptly becomes an electrical (but, not thermal)conductor at about 67° C. This temperature driven phase transition frominsulator-to-metal (IMT) occurs in a time scale of milliseconds (evennanoseconds). Furthermore, vanadium dioxide (lattice) crystal alsoundergoes a temperature driven structural phase transition, whereby whenheated the crystal rapidly contracts along one axis, while expandingalong the other two axes. Thus, vanadium dioxide can enable aminiaturized piezoelectric sensor/motor. The heating of the vanadiumdioxide to actuate as a miniaturized piezoelectric sensor/motor can bedone with a heating pad. Furthermore, as vanadium dioxide absorbs light,it converts into heat, thus the actuation can be triggeredopto-thermally.

Furthermore, a display component can include one or more embedded camerasensors (within a display pixel).

Details of the display component including one or more embedded camerasensors (within a display pixel) have been described/disclosed in FIGS.42A and 42B of U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019.

Further details of the display component including one or more embeddedcamera sensors (within a display pixel) have been described/disclosed inU.S. Non-Provisional patent application Ser. No. 16/602,404 entitled“SYSTEM AND METHOD OF AMBIENT/PERVASIVE USER/HEALTHCARE EXPERIENCE”,filed on Sep. 28, 2019 and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.Alternatively, an intelligent (smart) camera identifying an object inthe intelligent (smart) camera's field of view can be utilized, wherethe intelligent (smart) camera can include an (embedded) digital signalprocessor, a tunable (short/long) focal length metasurface (e.g.,utilizing thermally tunable refractive index of a phase transition/phasechange material) lens and a machine learning algorithm or an artificialneural network algorithm (ANN). The intelligent (smart) camera can alsoinclude an algorithm to classify an image and another algorithm totranslate language (in near real-time/real-time).

Alternatively, the camera sensor can be replaced/augmented by acomputational camera sensor, wherein the computational camera sensorincludes a laser and a photodiode (e.g., a PIN photodiode/avalanchephotodiode (APDysingle photon avalanche detector (SPAD)).

Details of the computational camera sensor (e.g., FIGS. 3L-3Z) have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Details of a holographic display component have been described/disclosedin FIG. 49 of U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019.

Further details of the holographic display component have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Further details of the holographic display component have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.14/999,601 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Jun. 1, 2016, (which resulted in aU.S. Pat. No. 9,923,124, issued on Mar. 20, 2018) and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Furthermore, a System-on-a-Chip, integrating a processor module andmodule specific software 760 with a graphic processor module, internetfirewall, spyware and the user-specific security control/authenticationcan simplify construction and fabrication of the intelligent appliance880.

Furthermore, a System-on-a-Chip can be replaced by a Super System onChip (SSoC) for fast (or ultrafast) data processing, imageprocessing/image recognition, deep learning/meta-learning, or/andself-learning;

-   -   wherein the Super System on Chip can include:    -   (i) a processor-specific electronic integrated circuit (EIC),        and/or    -   (ii) an array or a network of memristors for neural processing,    -   and/or    -   (iii) a photonic component or a photonic integrated circuit        (PIC), wherein the photonic component comprises an optical        waveguide,    -   wherein the processor-specific electronic integrated circuit in        said (i), the array or the network of memristors in said (ii)        and the photonic component or the photonic integrated circuit in        said (iii) of the Super System on Chip can be interconnected or        coupled in two-dimension (2-D) or in three-dimension (3-D)        electrically and/or optically. It should be noted that        atomically thin metal dichalcogenide/two-dimensional        semiconductor material (e.g., MoS₂, WS₂ and WSe₂) with        semimetallic bismuth as a contact layer can enable a high        performance processor-specific electronic integrated circuit,        extending Moore's law.

Details of the Super System on Chip have been described/disclosed (e.g.,FIGS. 15C-28B) in U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Further details of the Super System on Chip have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.14/999,601 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Jun. 1, 2016, (which resulted in aU.S. Pat. No. 9,923,124, issued on Mar. 20, 2018) and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

If the Super System on Chip can be coupled with a voice processingmodule-enabling a neural network/machine learning based voice processingmodule (a Super Voice Processing Module—that can also include semanticanalyzer. Powered by machine learning algorithms and natural languageprocessing, semantic analyzer can understand the context of a naturallanguage and/or detect emotion/sarcasm and extract valuable informationfrom unstructured data, achieving human-level accuracy.) The Super VoiceProcessing Module can be used for audio events identification, commanddetection, keyword spotting, speaker identification and wake worddetection. It can also support spoken words and can be programmed torecognize sounds.

The Super System on Chip can be coupled with a first artificial eye or asecond artificial eye. The first artificial eye can include lightactivated and/or electrically activated switches. The second artificialeye can include an array of photodiodes/optical capacitors.

For example, the artificial eye can be fabricated/constructed utilizinga very large scale integration of the atomic scaled switches.Photocurrent is induced in a photoconductive layer (which is coupledbetween a metal electrode and a solid-electrolyte electrode) by lightirradiation. The photocurrent reduces metal ions with positive chargesin the solid-electrolyte electrode and this precipitates as metal atomsto form an atomic scaled metal connection between the metal electrodeand the solid-electrolyte electrode-operating as an atomic scaledswitch, turned on by light irradiation and/or an applied electricalactivation (e.g., voltage).

Instead of a photoconducting layer, an array of (fast light) responsivephotodiodes (e.g., made of graphene or tungsten diselenide or othersuitable (fast light) responsive two-dimensional material) or an arrayof optical capacitors (e.g., made of p+ silicon substrate/silicondioxide/a perovskite material with a large photoconductiveresponse/semi-transparent metal electrode, wherein light is incidentthrough the semi-transparent metal electrode) can be utilized also. Theoptical capacitor can respond dynamically to light intensities.

It should be noted that an array of (fast light) responsive photodiodescoupled with phase transition/phase change material(electrically/optically controlled) based switches can enable a fastresponsive artificial eye.

Generally, a phase transition material is a solid material, wherein itslattice structure can change from a particular solid crystalline form toanother solid crystalline form, still remaining crystal-graphicallysolid. Generally, a phase change material is a material, wherein itsphase can change from (i) a solid to liquid or (ii) an amorphous tocrystalline structure or (iii) crystalline structure to amorphous.

The first artificial eye or the second artificial eye can be coupledwith a neural processor/Super System on Chip.

Details of the artificial eye have been described/disclosed in U.S.Non-Provisional patent application Ser. No. 16/602,404 entitled “SYSTEMAND METHOD OF AMBIENT/PERVASIVE USER/HEALTHCARE EXPERIENCE”, filed onSep. 28, 2019 and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.

Furthermore, the Super System on Chip can be coupled with a neuromorphicvisual system.

A neuromorphic visual system including optical resistive random accessmemory (ORRAM) based synaptic devices in a two-dimensional array canemulate/approximate basic functions of human visual system beyondvisible light.

For example, an optical resistive random access memory (ORRAM) basedsynaptic device can include an (i) optically (laser beam) coupledcapacitor of an oxide semiconductor material (e.g., amorphousindium-gallium-zinc oxide or molybdenum oxide) or (ii) optically (laserbeam) coupled field effect transistor of a two-dimensional material(e.g., molybdenum disulfide (MoS₂) or graphene) or a heterostructure oftwo distinct two-dimensional materials. An optically (laser beam)coupled capacitor of an oxide semiconductor material can be a sandwichstructure of a top transparent electrode (e.g., indium tin oxide)/middleoxide semiconductor material (e.g., amorphous indium-gallium-zinc oxideor molybdenum oxide)/a bottom non-transparent electrode on a substrate.

Optically (laser beam) coupling can be realized from laser beam(propagated via an optical waveguide) diffracted by gratings etched ontoan optical waveguide of an optical switch (e.g., a Mach-Zehnderinterferometer type optical switch).

The optical switch (laser beam switching) can include a phase changematerial or a phase transition material and it can be activated by adistinct pump optical signal of another wavelength or an electricalsignal (e.g., voltage or current).

To increase the intensity of laser beam, the oxide semiconductormaterial can be fabricated/constructed nanoscaled in size and placednear a plasmonic nanoantenna. Similarly, to increase the intensity oflaser beam, a source metal and a drain metal of the field effecttransistor of a two-dimensional material/heterostructure of two distincttwo-dimensional materials can be fabricated/constructed to form aplasmonic nanoantenna.

Details of a plasmonic nanoantenna have been described/disclosed inFIGS. 12H-12O of U.S. Non-Provisional patent application Ser. No.16/602,966 entitled “OPTICAL BIOMODULE TO DETECT DISEASES AT AN EARLYONSET”, filed on Jan. 6, 2020 and in its related U.S. non-provisionalpatent applications (with all benefit provisional patent applications)are incorporated in its entirety herein with this application.

Thus, a neuromorphic visual system can include (i) optically (laserbeam) coupled capacitor/field effect transistor, (ii) an optical switchand (iii) a plasmonic nanoantenna.

Furthermore, the Super System on Chip can be coupled with a radio(wireless) transceiver integrated circuit (e.g., 5G/higher than 5Gbandwidth radio (wireless) transceiver integrated circuit).

The Super System on Chip can be coupled with an intelligent algorithm,which includes a digital security protection (DSP) algorithm submodule,a natural language processing (NLP) algorithm submodule and anapplication specific algorithm submodule (the application specificalgorithm submodule is coupled with a public/consortium/privateblockchain). The application specific algorithm submodule and aknowledge database (the knowledge database is coupled with apublic/consortium/private blockchain) are coupled with a computer visionalgorithm submodule, a pattern recognition algorithm submodule, a datamining algorithm submodule, Big Data analysis algorithm submodule, astatistical analysis algorithm submodule, a fuzzy logic (includingneuro-fuzzy) algorithm submodule an artificial neural network/artificialintelligence algorithm submodule, a machine learning (including deeplearning/meta-learning and self-learning) algorithm submodule, apredictive analysis algorithm submodule, a prescriptive algorithm moduleand a software agent algorithm submodule.

The fusion of a neural network algorithm and fuzzy logic algorithm isneuro-fuzzy, which can enable both learning as well as approximation ofuncertainties. The neuro-fuzzy algorithm can use fuzzy inference engine(with fuzzy rules) for modeling uncertainties, which is further enhancedthrough learning the various situations with a radial basis function.The radial basis function consists of an input layer, a hidden layer andan output layer with an activation function of hidden units. Anormalized radial basis function with unequal widths and equal heightscan be written as:

${{\psi_{i}(x)}({softmax})} = \frac{\exp\left( h_{i} \right)}{\sum\limits_{i = 1}^{n}{\exp\left( h_{i} \right)}}$$h_{i} = \left( {- {\sum\limits_{l - 1}^{2}\frac{\left( {X_{l} - u_{il}} \right)^{2}}{2\sigma_{i}^{2}}}} \right)$X is the input vector, uil is the center of the ith hidden node (i=1, .. . , 12) that is associated with the lth (l=1, 2) input vector, σi is acommon width of the ith hidden node in the layer and softmax (hi) is theoutput vector of the ith hidden node. The radial basis activationfunction is the softmax activation function. First, the input data isused to determine the centers and the widths of the basis functions foreach hidden node. Second, it is a procedure to find the output layerweights that minimize a quadratic error between predicted values andtarget values. Mean square error can be defined as:

${MSE} = {\frac{1}{N}{\underset{k = 1}{\sum\limits^{N}}\left( {({TE})_{k}^{\exp} - ({TE})_{k}^{cal}} \right)^{2}}}$

The connections between various algorithm submodules of the intelligentalgorithm can be similar to synaptic networks to enable deeplearning/meta-learning and self-learning of the intelligent algorithm.Meta-learning can enable a machine some human-level mental agility. Itmay be useful for achieving machine intelligence at human-level.

Details of the intelligent algorithm have been described/disclosed inU.S. Non-Provisional patent application Ser. No. 16/602,404 entitled“SYSTEM AND METHOD OF AMBIENT/PERVASIVE USER/HEALTHCARE EXPERIENCE”,filed on Sep. 28, 2019 and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.

Further details of the intelligent algorithm have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.14/999,601 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Jun. 1, 2016, (which resulted in aU.S. Pat. No. 9,923,124, issued on Mar. 20, 2018) and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Furthermore, a super-capacitor (manufactured by www.cap-xx.com) and/orproton exchange membrane micro fuel-cell can enhance the operationaltime of a battery/solar cell/micro fuel-cell/wired power supplycomponent.

A foldable/stretchable display component can be constructed from agraphene sheet and/or an organic light-emitting diodeconnecting/coupling/interacting with a printed organic transistor and arubbery conductor (e.g., a mixture of carbon nanotube/gold conductor andrubbery polymer) with a touch/multi-touch sensor.

The foldable/stretchable display component can be rollable orreconfigurable/morphable in size.

Details of a foldable/stretchable/rollable display component have beendescribed/disclosed in FIG. 14B of U.S. Non-Provisional patentapplication Ser. No. 14/999,601 entitled “SYSTEM AND METHOD OFAMBIENT/PERVASIVE USER/HEALTHCARE EXPERIENCE”, filed on Jun. 1, 2016.

Further details of the foldable/stretchable/rollable display componenthave been described/disclosed in U.S. Non-Provisional patent applicationSer. No. 14/999,601 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Jun. 1, 2016, (which resulted in aU.S. Pat. No. 9,923,124, issued on Mar. 20, 2018) and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Details of a display component reconfigurable/morphable in size havebeen described/disclosed in FIGS. 18A-18B of U.S. Non-Provisional patentapplication Ser. No. 16/602,966 entitled “OPTICAL BIOMODULE TO DETECTDISEASES AT AN EARLY ONSET”, filed on Jan. 6, 2020.

Further details of the display component reconfigurable/morphable insize have been described/disclosed in U.S. Non-Provisional patentapplication Ser. No. 16/602,966 entitled “OPTICAL BIOMODULE TO DETECTDISEASES AT AN EARLY ONSET”, filed on Jan. 6, 2020 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

The intelligent appliance 880 includes a voice-to-text-to-voiceprocessing module and module specific software. (e.g., Crisp Sound isreal-time audio signal processing software for echo cancellation,background noise reduction, speech enhancement and equalization), avideo compression module and module specific software, a photo-editingsoftware module and a software module for automatically uploadingcontent to a preferred remote/cloud server.

The intelligent appliance 880 can be much thinner than 20 mm, if boththe display and battery components are thinner.

A thinner photonic crystal display component can be fabricated andconstructed as follows: optically pumping different-sized photoniccrystals, whereas the photonic crystals can individually emit blue,green and red light based on their inherent sizes. Optical pumping canbe generated from optical emission by electrical activation ofsemiconductor quantum-wells. Blue, green and red light can be thenmultiplexed/combined to generate white light.

Further details of the photonic crystal display component have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.14/999,601 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Jun. 1, 2016, (which resulted in aU.S. Pat. No. 9,923,124, issued on Mar. 20, 2018) and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

A thinner organic battery component can be fabricated and constructed asfollows: an organic battery utilizes push-pull organic molecules,wherein after an electron transfer process, two positively chargedmolecules are formed which are repelled by each other like magnets. Byinstalling a molecular switch, an electron transfer process can proceedin the opposite direction. Thus, forward and backward switching of anelectron flow can form the basis of an ultra-thin, light weight andpower efficient organic battery.

The intelligent appliance 880 can be integrated with a miniaturesurround sound (e.g., a micro-electrical-mechanical-system based siliconmicrophone component-Analog ADMP 401 or an equivalent component fromwww.akustica.com) module and module specific software, a miniature powerefficient projection (e.g., a holographic/micromirror projector) moduleand module specific software, an infrared transceiver module and modulespecific software and a biometric sensor (e.g., a fingerprint/retinalscan) module and module specific software.

A projection module can be miniaturized by utilizing one tilt-able 1 mmdiameter single crystal mirror. The mirror deflects a laser (blue, greenand red) beam by rapidly switching its angle of orientation, building upa picture pixel by pixel.

An array of (at least four) front-facing cameras can provide stereoviews and motion parallax (apparent difference in a direction ofmovement produced relative to its environment). Each camera can create alow dynamic range depth map. However, an array of cameras can create ahigh dynamic range depth map; thus, the intelligent appliance 880 canenable three-dimensional video conferencing.

The intelligent appliance 880 has multiple radio modules with multipleantennas. These multiple radio modules with multiple antennas can besimplified by a software-defined radio.

Augmented reality allows computer-generated content to be superimposedover a live camera-view in the real world. The intelligent appliance 880can be integrated with augmented reality to enrich the user's experienceand need.

The intelligent appliance 880 can be coupled with an augmented realityapparatus/augmented reality personal assistant apparatus.

Details of an augmented reality apparatus have been described/disclosedin FIGS. 51A, 51B, 51C, 51D, 52A, 52B, 52C, 52D and 53 in U.S.Non-Provisional patent application Ser. No. 16/602,404 entitled “SYSTEMAND METHOD OF AMBIENT/PERVASIVE USER/HEALTHCARE EXPERIENCE”, filed onSep. 28, 2019.

Further details of the augmented reality apparatus have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

The augmented reality personal assistant apparatus can include a camerasensor (wherein the camera sensor can provide atwo-dimensional/three-dimensional image/video, wherein the camera sensorcan be electro-optically coupled with one or more microlenses to imagesurrounding areas) and a display component (or a holographic displaycomponent).

Furthermore, a camera sensor can include a tunable focal length liquidlens. A sealed transparent (to an optical/viewing axis) optical cell cancontain two immiscible (e.g., water and oil) liquids, having equalphysical (not optical) densities. A pair of piezoelectric sensors/motorscan be mechanically coupled (perpendicular to the optical/viewing axis)with the sealed transparent (optical cell). By applying voltage inputsto each piezoelectric sensor/motor, mechanically coupled with the sealedtransparent (optical cell), the geometrical shape of one of theimmiscible liquids can be changed rapidly—making a variable/tunablefocal length (liquid) lens. In stead of a pair of piezoelectricsensors/motors, a pair of vanadium dioxide based piezoelectricsensors/motors can be used. Vanadium dioxide is an insulator at a roomtemperature, but abruptly becomes an electrical (but, not thermal)conductor at about 67° C. This temperature driven phase transition frominsulator-to-metal (IMT) occurs in a time scale of milliseconds (evennanoseconds). Furthermore, vanadium dioxide (lattice) crystal alsoundergoes a temperature driven structural phase transition, whereby whenheated the crystal rapidly contracts along one axis, while expandingalong the other two axes. Thus, vanadium dioxide can enable aminiaturized piezoelectric sensor/motor. The heating of the vanadiumdioxide to actuate as a miniaturized piezoelectric sensor/motor can bedone with a heating pad. Furthermore, as vanadium dioxide absorbs light,it converts into heat, thus the actuation can be triggeredopto-thermally.

Alternatively, the camera sensor can be replaced/augmented by acomputational camera sensor, wherein the computational camera sensorincludes a laser and a photodiode (e.g., a PIN photodiode/avalanchephotodiode (APD)/single photon avalanche detector (SPAD)).

Details of the computational camera sensor (e.g., FIGS. 3L-3Z) have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

The augmented reality personal assistant apparatus can also include avoice processing module (a module consists of one or more electroniccomponents) to process a voice command or an audio input.

Details of an augmented reality personal assistant apparatus have beendescribed/disclosed in FIGS. 17A-17C of U.S. Non-Provisional patentapplication Ser. No. 16/602,966 entitled “OPTICAL BIOMODULE TO DETECTDISEASES AT AN EARLY ONSET”, filed on Jan. 6, 2020.

Further details of the augmented reality personal assistant apparatushave been described/disclosed in U.S. Non-Provisional patent applicationSer. No. 16/602,966 entitled “OPTICAL BIOMODULE TO DETECT DISEASES AT ANEARLY ONSET”, filed on Jan. 6, 2020 and in its related U.S.non-provisional patent applications (with all benefit provisional patentapplications) are incorporated in its entirety herein with thisapplication.

The intelligent appliance 880 can acquire information on abarcode/RFID/near-field communication tag on a product by utilizing itsradio module. The intelligent appliance 880 is aware of its location viaits indoor/outdoor position module (within the radio module and modulespecific software 640) and it can search for a price/distributionlocation. Thus, the intelligent appliance 880 can enable a real-worldphysical search.

The intelligent appliance 880 can enable content over-IP (e.g., Skypeservice) via an ambient Wi-Fi/Wi-Max network, thus disrupting thetraditional carrier controlled cellular business model.

Near-field communication has a short range of about 35 mm-making it anideal choice for a contact-less (proximity) application. A near-fieldcommunication module (with an antenna) and module specific software 680can allow the user to learn/exchange/transfer/share/transact in acontactless (proximity) application in real-time. A standalonenear-field communication enabled micro-subsystem (e.g., a SD/SIM cardform factor) can integrate an IP/micro IP/light weight IP address moduleand module specific software 500, the storage/memory module and modulespecific software 780, the near-field communication module (with anantenna) and module specific software 680 and the software module 700.To exchange/transfer/share/transact content, the radio module and modulespecific software 640 can be integrated with a standalone near-fieldcommunication enabled micro subsystem. To enhance the security of thestandalone near-field communication enabled micro-subsystem, the sensormodule (e.g., a 0.2 mm thick fingerprint sensor component (manufacturedby Seiko Epson) reads an electric current on the user's finger tipcontact or a sensor component is uniquely synchronized with anothersensor component) and module specific software 820 can be integrated.Furthermore, an advanced biometric (fingerprint) sensor module can befabricated/constructed by combining a silica colloidal crystal withrubber, wherein the silica colloidal crystal can be dissolved in dilutehydrofluoric (HF) acid-leaving air voids in the rubber, thus creating anelastic photonic crystal. An elastic photonic crystal emits an intrinsiccolor, displaying three-dimensional shapes of ridges, valleys and poresof a fingerprint, when pressed. The processor module and module specificsoftware 760 can be utilized to compare with the user's captured/storedfingerprint data. Non-matching fingerprint data would render thestandalone near-field communication enabled micro-subsystem unusable incase of an abuse/fraud/theft.

The intelligent appliance 880 can include a sketch pad electronic moduleand a stylus, wherein the sketch pad electronic module include anelectronic circuitry for capacitive coupling, a transparent input matrixcomponent and a write-erase switch.

Details of the sketch pad electronic module have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.13/448,378 entitled “SYSTEM AND METHOD FOR MACHINE LEARNING BASED USERAPPLICATION”, filed on Apr. 16, 2012 and in its related U.S.non-provisional patent applications (with all benefit provisional patentapplications) are incorporated in its entirety herein with thisapplication.

The intelligent appliance 880 can also a personal awareness assistantelectronic module, wherein the personal awareness electronic moduleincludes a microphone and/or an audio recorder

The personal awareness assistant electronic module categorizesinformation or data received by the personal awareness assistantelectronic module into a database.

Details of the personal awareness assistant electronic module have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.13/448,378 entitled “SYSTEM AND METHOD FOR MACHINE LEARNING BASED USERAPPLICATION”, filed on Apr. 16, 2012 and in its related U.S.non-provisional patent applications (with all benefit provisional patentapplications) are incorporated in its entirety herein with thisapplication.

Five critical contactless (proximity) applications are: (a)product/service discovery/initiation, (b) peer-to-peerexchange/transfer/share/transaction, (c) machine-to-machineexchange/transfer/share/transaction, (d) remote access of anappliance/subsystem/system/terminal and (e) access authentication.

Product/Service Discovery/Initiation

The standalone near-field communication enabled micro-subsystem, incontactless proximity of another near-field communication enabledappliance/subsystem/system/terminal, receives a URL (web site) to (a)provide information about a product/service, (b) receive direct and/orpeer-to-peer marketing (e.g., coupon/advertisement/promotion/brandloyalty program) and (c) monitor/measure the effectiveness of amarketing campaign.

Peer-To-Peer Exchange/transfer/Share/Transaction

The user can share social network/businessprofile/microloan/microcontent in contactless proximity of thenear-field communication enabled appliance/subsystem/system/terminal ofanother user.

Machine-to-Machine Exchange/Transfer/Share/Transaction

The user can transact money/microloan/microcontent in contactlessproximity of a near-field communication enabledappliance/subsystem/system/terminal.

An example, the standalone near-field communication enabledmicro-subsystem can enable printing a stored photo, in contactlessproximity of a near-field communication enabled printer and displaying astored movie, in contact-less proximity of a near-field communicationenabled TV.

A near-field communication enabled TV can be fabricated and constructedsimilarly to the intelligent appliance 880.

Another example, the standalone near-field communication enabledmicro-subsystem can enable purchasing a travel ticket, in contactlessproximity of a near-field communication enabled ticketappliance/subsystem/system/terminal. Such a ticket can be verifiedand/or located by an indoor position module without need of human input.

Another example, a near-field communication enabled a printer moduleintegrated with an electro-mechanical weighing module, anelectro-mechanical postage dispensing module and a software module forcalculating the postage price based on weight, distance, priority leveland delivery method can enable purchasing postage efficiently.

Remote (Appliance/Subsystem/System/Terminal) Access

The user's profile, bookmarks, address book, preferences, settings,applications and contents of an appliance/subsystem/system/terminalcould be stored securely in the standalone near-field communicationenabled micro-subsystem, in contactless proximity of a near-fieldcommunication enabled appliance/subsystem/system/terminal, it will loadan original version of the user's profile, bookmarks, address book,preferences, settings, applications and content.

Access Authentication

The user can utilize the standalone near-field communication enabledmicro-subsystem, in contactless proximity of a near-field communicationenabled appliance/subsystem/system/terminal to enable authentication ofan appliance/subsystem/system/terminal.

The standalone near-field communication enabled micro-subsystem (asdiscussed above) can be integrated (by inserting into anelectro-mechanical socket) with the intelligent appliance 880.

Direct marketing (e.g., coupon/advertisement/promotion/brand loyaltyprogram) exists via AdMob and Groupon. A static social network existsvia MySpace and Facebook. The primary motivation of the user is socialconnections with other users in a social network website. However, a webbased social network can limit a human bond.

The standalone near-field communication enabledmicro-subsystem/intelligent appliance can enable an off-line socialexchange and direct and/or peer-to-peer marketing.

A personalized social network can utilize an augmented identity (e.g.,Recognizr) in addition to a profile. A personalized social network cankeep track of information/discussion/interests, which are important tothe user/users and make such information/discussion/interests availableto the user/users when the user/users are either on-line and/off-line.

Direct marketing can be segmented by demographics/geographical locations(e.g., gender/maritalstatus/age/religion/interests/education/work-positionincome/creditprofile/net asset/zip code). However, adding real-time geographicallocation to direct marketing can be useful (e.g., the user close to astadium and minutes before an event can purchase a ticket and after anevent can receive direct marketing based on the user'sinterests/preferences/patterns. This is personalized marketing)

Personalization can be enhanced by the intelligence rendering softwaremodule 700 (e.g., a machine learning/iterative learn-by-doing/naturallearning algorithm in a software module). The intelligent software agent(a do-engine) can search the internet automatically and recommend to theuser a product/service/content based on the user'sinterests/preferences/patterns. Integration of the user's social networkprofile, the user's interests/preferences/patterns, the user's real-timegeographical location, data/information/images from the objects 720 andinteraction (of the objects 720 s with the intelligent subscribersubsystem 340 and the intelligent appliance 880) collectively can embedphysical reality into internet space and internet reality into aphysical space thus, it can enrich the user's experience and need.

FIG. 7 illustrates a method flow-chart enabling an intelligent, locationbased and personalized social network, which can be realized byincluding at least the following steps: (a) authenticating the user1000, (b) understanding the user's profile (an augmented identity ispreferred) 1020, (c) remembering the user's need 1040, (d) rememberingthe user's conversation 1060, (e) reminding the user's need 1080, (f)determining the user's location (real-time is preferred) 1100, (g)searching the internet for the user's need (the intelligent softwareagent is preferred) 1120, (h) recommending a product/service best suitedfor the user's need 1140, (i) developing a learning algorithm 1300(e.g., a machine learning/iterative learning-by-doing/natural learningalgorithm in the software module 700) from a plurality of the users'activities, (j) utilizing a learning algorithm 1320 and (k) re-iteratingall previous steps from (a) to (j) in a loop cycle 1340.

FIG. 8 illustrates a method flow-chart enabling intelligent, locationbased and personalized direct marketing (e.g.,coupon/advertisement/promotion/brand loyalty program) by including atleast the following steps: (a) authenticating the user 1000, (b)understanding the user's profile (an augmented identity is preferred)1020, (c) remembering the user's need 1040, (d) remembering the user'sconversation 1060, (e) reminding the user's need 1080, (f) determiningthe user's location (real-time is preferred) 1100, (g) searching theinternet for the user's need (the intelligent software agent ispreferred) 1120, (h) delivering direct marketing material (e.g.,coupon/advertisement/promotion/brand loyalty program) based on theuser's need 1160, (i) developing the learning algorithm 1300 (e.g., amachine learning/iterative learning-by-doing/natural learning algorithmin the software module 700) from the plurality of users' activities, (j)utilizing the learning algorithm 1320 and (k) re-iterating all previoussteps from (a) to (j) in a loop cycle 1340.

A method of enabling intelligent, location based and personalizedpeer-to-peer marketing (e.g., coupon/advertisement/promotion/brandloyalty program) can be realized by including at least the steps: (a)authenticating the user 1000, (b) understanding the first user's profile(an augmented identity is preferred) 1020, (c) authenticating a seconduser 1000A, (d) understanding the second user's profile (an augmentedidentity is preferred) 1020A, (e) determining the first user's location(real-time is preferred) 1100, (f) determining the second user'slocation (real-time is preferred) 1100A, (g) communicating and/orsharing with a plurality of users for a collective need (an augmentedidentity is preferred) 1180, (h) determining the users' locations(real-time is preferred) 1100B, (i) delivering marketing material (e.g.,coupon/advertisement/promotion/brand loyalty program) from the firstuser to the second user and/or users, seeking marketing material (e.g.,coupon/advertisement/promotion/brand loyalty program) 1160A, (j)developing the learning algorithm 1300 (e.g., a machinelearning/iterative learning-by-doing/natural learning algorithm in thesoftware module 700) from a plurality of the users' activities, (k)utilizing the learning algorithm 1320 and (o) re-iterating all previoussteps from (a) to (k) in a loop cycle 1340.

A method of enabling an intelligent, location based and personalizedpeer-to-peer microloan transaction can be realized by including at leastthe steps: (a) authenticating the user 1000, (b) understanding the firstuser's profile (an augmented identity is preferred) 1020, (c)authenticating a second user 1000A, (d) understanding the second user'sprofile (an augmented identity is preferred) 1020A, (e) determining thefirst user's location (real-time is preferred) 1100, (f) determining thesecond user's location (real-time is preferred) 1100A, (g) communicatingand/or sharing with a plurality of the users for a collective need (anaugmented identity is preferred) 1180, (h) determining the users'locations (real-time is preferred) 1100B, (i) determining legalparameters of a microloan 1200, (j) agreeing on legal parameters of themicroloan 1220, (k) establishing a security protocol between the firstuser and the second user and/or users, seeking the microloan 1240, (l)delivering the microloan from the first user to the second user and/orusers, seeking the microloan 1160B, (m) developing the learningalgorithm 1300 (e.g., a machine learning/iterativelearning-by-doing/natural learning algorithm in the software module 700)from a plurality of the users' activities, (n) utilizing the learningalgorithm 1320 and (o) re-iterating all previous steps from (a) to (n)in a loop cycle 1340.

A method of enabling an intelligent, location based and personalizedpeer-to-peer microcontent transaction can be realized by including atleast the steps: (a) authenticating the user 1000, (b) understanding thefirst user's profile (an augmented identity is preferred) 1020, (c)authenticating a second user 1000A, (d) understanding the second user'sprofile (an augmented identity is preferred) 1020A, (e) determining thefirst user's location (real-time is preferred) 1100, (f) determining thesecond user's location (real-time is preferred) 1100A, (g) communicatingand/or sharing with a plurality of users for a collective need (anaugmented identity is preferred) 1080, (h) determining the users'locations (real-time is preferred) 1100B, (i) determining legalparameters of microcontent transfer 1200 (j) agreeing on legalparameters of the microcontent transfer 1220, (k) establishing asecurity protocol between the first user and the second user and/orusers, seeking the microcontent transfer 1240, (l) delivering themicrocontent from the first user to the second user and/or users,seeking the microcontent 1160C, (m) developing the learning algorithm1300 (e.g., a machine learning/iterative learning-by-doing/naturallearning algorithm in the software module 700) from a plurality of theusers' activities, (n) utilizing the learning algorithm 1320 and (o)re-iterating all previous steps from (a) to (n) in a loop cycle 1340.

FIG. 9 illustrates a method flow-chart enabling intelligent, locationbased and personalized secure contactless (proximity) internet accessauthentication can be realized by including at least the steps of: (a)authenticating the user 1000, (b) determining the first user's location(real-time is preferred) 1100, (b) coming in proximity of a near-fieldenabled appliance/subsystem/system/terminal 1260, (c) authenticating theuser for the internet 1280, (d) developing the learning algorithm 1300(e.g., a machine learning/iterative learning-by-doing/natural learningalgorithm in the software module 700) from a plurality of users'activities, (e) utilizing the teaming algorithm 1320 and (f)re-iterating all previous steps from (a) to (e) in a loop cycle 1340.

An intelligent software agent can also search the internet automaticallyand recommend to the user a product/service/content based on the user'sinterests/preferences/patterns. The intelligence rendering softwarealgorithm in the software module 700, allows the intelligent subscribersubsystem 340 and the intelligent appliance 880 to adapt/learn/relearnthe user's interests/preferences/patterns, thereby renderingintelligence.

For example, a bedroom clock connects/couples/interacts with theintelligent subscriber subsystem 340 and/or the intelligent appliance880 to automatically check on a traffic pattern/flight schedule via theinternet, before deciding whether to fiddle with an alarm time withouthuman input. When a rechargeable toothbrush detects a cavity in theteeth, it sends a signal through its electrical wiring andconnects/couples/interacts with the intelligent subscriber subsystem 340and/or the intelligent appliance 880, automatically accesses a locationbased/assisted dentist's electronic appointment book for a consultationwithout human input.

The intelligent appliance 880 can include or couple with a spatialcomputing system.

A spatial computing system can generally include virtual reality (VR)application, augmented reality (AR) application, mixed realityapplication (MR), digitized items with sensors (e.g., voice/audiocontrol, eye tracking, hand/body tracking a camera sensor, a hapticfeedback system, a LiDAR sensor for measuring distances with laser lightand making three-dimensional representation in line of sight and innon-line of sight, Global Positioning System (GPS) and a geolocationsensor), real-time video, robotic system, the Internet of Things (IoT),computer implementable artificial intelligence/machine learninginstructions/algorithm, computer implementable machine visioninstructions/algorithm and computer implementable predictiveinstructions/algorithm connected via a cloud server—enabling thesensors/machines/motors to couple with each other in nearreal-time/real-time, thus creating an extended reality (XR) for human tomachine and machine to machine interactions. For example, a digitalfloor plan of a house can be integrated with a digitally cataloged mapof all items (including the connected sensors) in the house, as anelderly person moves through the house, the lights in the elderlyperson's path will automatically switch on and off, the table will moveby itself to improve access to a refrigerator. The furniture will moveby itself to protect the elderly person from falling, whilesimultaneously alerting the family member/911 emergency or an integratedmonitoring station.

A spatial computing system can enable physical space to send an inputrequest to a computer and receive an output recommendation from thecomputer.

The intelligent appliance 880 can integrate a chemical/biosensor module(e.g., to monitor/measure body temperature, % oxygen, heart rhythm bloodglucose concentration, carbonyl sulfide gas emission due to a liver/lungdisease and a biomarker for a disease parameter) with module specificsoftware.

A zinc oxide nanostructure can detect many toxic chemicals. Also, aquantum cascade DFB/DBR/DR laser (with an emission wavelength inmid-to-far infrared range) can detect a part per billion amount ofcarbonyl sulfide gas. Wavelength switching of a quantum cascadeDFB/DBR/DR laser can be achieved by temperature, utilizing a thin-filmresistor/heater, while electrically insulating a laser bias currentelectrode. Wavelength switching by temperature is a slow (about tenmilliseconds) thermal process. However, wavelength switching byelectrical currents on multiple segments of a quantum cascade DFB/DBR/DRlaser is a rapid (about one millisecond) process. A larger wavelengthtuning range (nm) can be achieved by an array (a monolithic array ispreferred) of multi-segment quantum cascade DFB/DBR/DR lasers.Furthermore, a quantum cascade DFB/DBR/DR laser can emit in terahertzwavelength (85 μm to 150 μm) range, where a metal has a highreflectivity. Thus, a quantum cascade DFB/DBR/DR laser is ideal formetal detection (security).

A compact biomarker-on-a-chip to monitor/measure a disease parameter canbe fabricated and constructed by analyzing a change in reflectanceand/or a Raman shift and/or surface electric current due to adisease-related biomarker presence (with a specific antibody at about apicogram per mL concentration) on a surface of atwo-dimensional/three-dimensional photonic crystal of dielectricmaterial. Confirmation of a single biomarker is not conclusive for theonset/presence of a disease. Identifications of many biomarkers arenecessary to predict the onset/presence of a disease. However, atwo-dimensional/three-dimensional photonic crystal of dielectricmaterial, incident with a multi-wavelength (blue, green and red) lightsource can be utilized for simultaneous identifications of manybiomarkers of a disease. A multi-wavelength (blue, green and red) lightsource can be fabricated and constructed as follows: optically pumpingdifferent-sized photonic crystals, whereas the photonic crystals canindividually emit blue, green and red light based on their inherentsizes. Optical pumping can be generated from optical emission byelectrical activation of semiconductor quantum-wells. Blue, green andred light can be multiplexed/combined to generate white light. A Ramanshift scattered by the biomarker requires an expensive high-performancelaser. However, a Raman sensor (requires an inexpensive CD laser and awavelength tunable filter) can monitor/measure a Raman shift due to adisease-related biomarker presence. A biomarker molecule can induce achange in surface induced electric current when it binds to anatomically thin graphene surface (graphene's electronic sensitivity tobiomolecular adsorption). Thin graphene surface may contain grapheneoxide.

Alternatively, a surface-enhanced Raman spectroscopy (SERS) based Ramanprobe can be adopted, utilizing a substrate (e.g., a graphene/grapheneoxide substrate), a miniature spectrophotometer and a laser (e.g., a 785nm laser) to detect a presence of a disease-related biomarker.

A surface-enhanced Raman spectroscopy specific laser can be (i) asingle-longitudinal mode (SLM) laser or (ii) a distributed feedback(DFB)/distributed Bragg reflection (DBR) diode laser or (iii) a volumeBragg-grating (VBG) frequency-stabilized diode laser.

A surface-enhanced Raman spectroscopy specific miniaturespectrophotometer can be spectrophotometer-on-a-chip, which is based oncascaded series of arrayed waveguide grating routers (AWGR).

The substrate can have an array or a network of three-dimensional(metal) structures or three-dimensional protruded optical nanoantennasto enhance surface-enhanced Raman spectroscopy based Raman signal.

Details of a three-dimensional (metal) structure(s) have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,966 entitled “OPTICAL BIOMODULE TO DETECT DISEASES AT AN EARLYONSET”, filed on Jan. 6, 2020 and in its related U.S. non-provisionalpatent applications (with all benefit provisional patent applications)are incorporated in its entirety herein with this application.

Details of a three-dimensional (metal) structure(s) have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.15/731,577 entitled “OPTICAL BIOMODULE TO DETECT DISEASES AT AN EARLYONSET”, filed on Jul. 3, 2017 and in its related U.S. non-provisionalpatent applications (with all benefit provisional patent applications)are incorporated in its entirety herein with this application.

Details of a three-dimensional (metal structure(s)) have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.13/663,376 entitled “OPTICAL BIOMODULE TO DETECT DISEASES”, filed onOct. 29, 2012 and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.

Examples of three-dimensional protruded optical nanoantennas have beendescribed/disclosed in FIGS. 12H-12O3 of U.S. Non-Provisional patentapplication Ser. No. 16/602,906 entitled “OPTICAL BIOMODULE TO DETECTDISEASES AT AN EARLY STAGE”, filed on Jan. 6, 2019.

Further details of the three-dimensional protruded optical nanoantennashave been described/disclosed in U.S. Non-Provisional patent applicationSer. No. 16/602,906 entitled “OPTICAL BIOMODULE TO DETECT DISEASES AT ANEARLY STAGE”, filed on Jan. 6, 2019 and in its related U.S.non-provisional patent applications (with all benefit provisional patentapplications) are incorporated in its entirety herein with thisapplication.

However, surface-enhanced Raman spectroscopy hot spot is generally lessthan 10 nm and a biomarker (e.g., bacteria/virus) is generally muchlarger in diameter than 10 nm. This size mismatch can yield poorreliability in detection of a biomarker.

A volume-enhanced Raman spectroscopy (VERS) based Raman probe signal ofa biomarker can be obtained within a fluidic container, utilizingparamagnetic magnetic nanoparticles, Raman active molecules (whereineach Raman active molecule is functionalized with a biomarkerselective/specific biomarker binder), a miniature spectrophotometer anda laser.

Alternatively, silver nanoparticles labeled with Raman active molecules(wherein each Raman active molecule is functionalized with a biomarkerselective/specific biomarker binder) can be mixed with a biomarker. Thismixture can propagate through a fluidic channel (alternatively, thefluidic channel can have an array of angled (about 70 degree angle)silver nanorods, without the need of silver nanoparticles in the firstplace) at the focus of a laser to generate surface-enhanced Ramanspectroscopy signal by the Raman active molecules.

In general, a Raman probe can include either a surface-enhanced Ramanspectroscopy based Raman probe or a volume-enhanced Raman spectroscopy(VERS) based Raman probe.

Alternative to Raman sensor/Raman probe, a Förster resonance energytransfer (FRET) based probe can be utilized, which includes a laser, aphotodetector and an optical filter. Furthermore, Förster resonanceenergy transfer signal can be enhanced significantly in presence of oneor more (or an array of) three-dimensional (metal) structures orprotruded optical nanoantennas, optimized for (i) donor'sabsorption-emission spectrum and (ii) acceptor's absorption-emissionspectrum.

Details of the Förster resonance energy transfer based probe have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,966 entitled “OPTICAL BIOMODULE TO DETECT DISEASES AT AN EARLYONSET”, filed on Jan. 6, 2020 and in its related U.S. non-provisionalpatent applications (with all benefit provisional patent applications)are incorporated in its entirety herein with this application.

Further details of the Förster resonance energy transfer based probe(e.g., FIGS. 57I-57K) have been described/disclosed in U.S.Non-Provisional patent application Ser. No. 16/602,404 entitled “SYSTEMAND METHOD OF AMBIENT/PERVASIVE USER/HEALTHCARE EXPERIENCE”, filed onSep. 28, 2019 and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.

The above Raman sensor/Raman probe/Förster resonance energy transferbased probe may detect a presence of a disease-related biomarker in avirus laden pandemic.

Alternative to the above Raman sensor/Raman probe/Förster resonanceenergy transfer based probe, an electrochemical cell with an array ofelectrodes (wherein the electrochemical cell is furtherintegrated/included with a microfluidic channel to separate plasma/serumfrom whole blood) can be utilized to measure electrical impedance todetect a presence of a disease-related biomarker in a virus ladenpandemic.

Details of an electrochemical cell have been described/disclosed in U.S.Non-Provisional patent application Ser. No. 16/602,966 entitled “OPTICALBIOMODULE TO DETECT DISEASES AT AN EARLY ONSET”, filed on Jan. 6, 2020and in its related U.S. non-provisional patent applications (with allbenefit provisional patent applications) are incorporated in itsentirety herein with this application.

The above Raman sensor/Raman probe/Förster resonance energy transferbased probe can enable location based autonomous reporting/autonomouscontact tracing, when it is coupled with the intelligent appliance 880and/or a wearable device to measure health parameters (e.g., bodytemperature, oxygen saturation, heart rate and blood pressure).

Details of a wearable device have been described/disclosed in U.S.Non-Provisional patent application Ser. No. 16/602,404 entitled “SYSTEMAND METHOD OF AMBIENT/PERVASIVE USER/HEALTHCARE EXPERIENCE”, filed onSep. 28, 2019 and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.

Furthermore, an array of graphene biosensors can detect many biomarkersof a disease thus, enabling a personalized ultra-compact diagnosticmodule, which can be connected/coupled/interacted with the intelligentsubscriber subsystem 340 and the intelligent appliance 880.

A biological lab-on-a-chip (LOC) is a module that integrates a fewbioanalytical functions on a single chip to perform point-of-caredisease diagnostics. A miniature biological lab-on-a-chip modulemanufactured by Ostendum (www.ostendum.com) can be integrated (byinserting into an electro-mechanical cavity) with the intelligentappliance 880 to perform point-of-care disease diagnostics reliably,quickly and economically. Such a lab result can be transmitted from theintelligent appliance 880 to a location based/assisted physician forinterpretation without human input. Furthermore, electrically powered bya nano-generator, zinc oxide nanowires fabricated on galliumnitride/indium gallium nitride/aluminum gallium nitride can be ananolight source for a biological lab-on-a-chip.

The biological lab-on-a-chip can include (i) a light source (e.g., alaser of a suitable wavelength and/or (ii) a photodetector to detect asuitable wavelength and/or (iii) an optical filter to transmit/block asuitable wavelength and/or (iv) a microfluidic channel topropagate/separate/store a biological fluid (e.g., serum/plasma)containing a disease biomarker (e.g., a microRNA (miRNA)-tiny RNA is onaverage about 22 nucleotides long or an exosome) and a complementarydisease biomarker binder (e.g., a sequence of oligonucleotides), whereinthe complementary disease biomarker binder can bind/couple with thedisease biomarker.

The complementary disease biomarker binder can also include one or morefluorophores. Furthermore, two fluorophores (in about 10 nm proximity)can be designed to obtain Förster resonance energy transfer (FRET).

The microfluidic channel can also include an array of three-dimensionalprotruded optical nanoantennas (NOAs) to enhance Förster resonanceenergy transfer/efficiency.

Examples of three-dimensional protruded optical nanoantennas have beendescribed/disclosed in FIGS. 12H-12O3 of U.S. Non-Provisional patentapplication Ser. No. 16/602,906 entitled “OPTICAL BIOMODULE TO DETECTDISEASES AT AN EARLY STAGE”, filed on Jan. 6, 2019.

Further details of the three-dimensional protruded optical nanoantennashave been described/disclosed in U.S. Non-Provisional patent applicationSer. No. 16/602,906 entitled “OPTICAL BIOMODULE TO DETECT DISEASES AT ANEARLY STAGE”, filed on Jan. 6, 2019 and in its related U.S.non-provisional patent applications (with all benefit provisional patentapplications) are incorporated in its entirety herein with thisapplication.

The microfluidic channel can also include a substrate of two or morematerials-including, but not limited to a metamaterial (e.g.Epsilon-Near-Zero (ENZ) metamaterial) of exceptional optical properties.

Alternatively, the biological lab-on-a-chip can include a nanopore basedDNA/RNA sequencing biomodule which includes a molecular system(including nucleotides-nucleotides which make up DNA utilizing adenine(A), thymine (T), cytosine (C), and guanine (G). In RNA, the thymine isreplaced with uracil (U)) to be sensed, a nanohole (for passing themolecular system to be sensed) of about less than 10 nm in diameter(however, the nanohole is typically about 1.5 nm in diameter) and anelectronic circuit electrically coupled with the nanohole to measureelectrical signals related to the nucleotides.

The above nanopore based DNA/RNA sequencing biomodule can enablelocation based autonomous reporting/autonomous contact tracing, when itis coupled with the intelligent appliance 880 and/or a wearable deviceto measure health parameters (e.g., body temperature, oxygen saturation,heart rate and blood pressure).

Details of a nanopore based DNA/RNA sequencing biomodule have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.13/663,376 entitled “OPTICAL BIOMODULE TO DETECT DISEASES”, filed onOct. 29, 2012 and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.

Holographic images of the user's genes/proteins can be stored in theintelligent appliance 880 and such holographic images can enable aphysician/surgeon to design a personalized medical and/or surgicaltreatment.

Furthermore, the intelligent appliance 880 can store a user's encryptedheath data, coupled with a blockchain. The intelligent appliance 880 cantransmit the user's encrypted heath data (coupled with a blockchain) toa medical professional (e.g., a doctor).

Details of a user's encrypted heath data, coupled with a blockchain havebeen described/disclosed in U.S. Non-Provisional patent application Ser.No. 16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Furthermore, the intelligent appliance 880 coupled with the biologicallab-on-a-chip can be utilized for a cloud based healthcare system (e.g.,telemedicine or telehealth, which is the distribution of health-relatedservices and information over the internet without any physicalpresence).

An example of a cloud based healthcare system have beendescribed/disclosed in FIGS. 3G1 & 3G2 of U.S. Non-Provisional patentapplication Ser. No. 16/873,634 entitled “SYSTEM AND METHOD FOR MACHINELEARNING AND AUGMENTED REALITY BASED USER APPLICATION”, filed on May 26,2020.

Further details of the cloud based healthcare system have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/873,634 entitled “SYSTEM AND METHOD FOR MACHINE LEARNING ANDAUGMENTED REALITY BASED USER APPLICATION”, filed on May 26, 2020 and inits related U.S. non-provisional patent applications (with all benefitprovisional patent applications) are incorporated in its entirety hereinwith this application.

Many software modules, as discussed above can consume significantelectrical power due to computational complexities. Alternatively, manysoftware modules can be processed at a secure remote/cloud server.Software modules can be embedded within the intelligent subscribersubsystem 340 and/or the intelligent appliance 880, if electrical powerconsumption and/or thermal management are feasible. Effective thermalmanagement is critical to fabricate and construct a high-performanceintelligent appliance 880. Thermal resistance must be minimized at allmaterial interfaces and materials with closely matching thermalexpansion coefficients must be used.

Graphene can be viewed as a plane of carbon atoms extracted from agraphite crystal. Multiple-atomic layers of graphene are easier tofabricate than a single-atomic layer graphene and multiple-atomic layersof graphene retain thermal conductivity of a single-atomic layergraphene. A nanoscaled graphene heat pipe can be utilized to cool a hotspot within the intelligent appliance 880. For efficient thermalmanagement, a heat sink/heat spreader of graphene/diamond/aluminumnitride/copper/aluminum/silicon/material with closely matching thermalexpansion coefficients can be attached (e.g., to the processor module760) by utilizing an interface heat transfer material (e.g., Indigo™www.enerdynesolutions.com). However, a significant (about 10×) heattransfer of a heat sink/heat spreader can be gained by creating ananostructured (e.g., zinc oxide nanostructures fabricated bymicroreactor assisted nanomaterial deposition process) surface on theheat sink/heat spreader. Furthermore, microchannels can be fabricated bya laser machining method onto the heat sink/heat spreader for passiveair and/or active (air/liquid/micro-scale ion cloud) cooling.

A microscaled ion cloud can be generated as follows: on one side ofgraphene based microchannels is a carbon nanotube negative electrode,when a negative voltage is switched on, electrons jump from a negativeelectrode toward a positive electrode, colliding with air molecules neara hot spot thus, dissipating heat and producing a microscale cloud ofpositively charged ions. A microscale cloud of positively charged ionsdrifts towards a present negative electrode. However, before it reachesthe present negative electrode, voltage is switched on to anothernegative electrode at a different position. Forward and reverse wind ofa microscale cloud of positively charged ions (created by changing thepositions of negative electrodes) can cool a hot spot within theintelligent appliance 880. Alternatively, high-efficiency nanostructured50 A° thick Sb₂Te₃/10 A° thick Bi₂Te₃-based thin-film superlatticesthermoelectric cooler (TEC)/microrefrigerator (1 mm×3 mm) can also beutilized to cool a hot spot within the intelligent appliance 880.However, significant thermoelectric cooler (TEC)/microrefrigeratorefficiency can be gained by fabricating a quantum wire/quantum dot,transitioning from a two-dimensional superlattice.

Furthermore, the intelligent appliance 880 can be charged via resonantelectromagnetic inductive coupling energy transfer without a physicalwire.

Aluminum/magnesium alloys have small building blocks-called nanocrystalgrains with crystal defects. Nanocrystal grains with crystal defects aremechanically stronger than perfect aluminum/magnesium crystals. Theintelligent appliance 880's outer package can be constructed from ananoengineered aluminum/magnesium alloy, Liquid Metal® alloy(www.liquidmetal.com), a carbon-polymer composite (carbon fiber embeddedwith a molten polymer injection mold) and magnesium metal. Furthermore,an antenna can be constructed from a carbon fiber embedded with ametal/conducting polymer.

FIG. 10 illustrates a block diagram ofconnections/couplings/interactions (viaelectrical/optical/radio/sensor/biosensor communication network(s))between the object(s) 720 with the intelligent subscriber subsystem(s)340 and the intelligent appliance(s) 880, utilizing internet protocolversion 6 (IPv6) and its subsequent versions. The context-awareness is(according to the user's situational context), personalized (tailored tothe user's need), adaptive (changes in response to the user's need) andanticipatory (can anticipate the user's desire).

The intelligent subscriber subsystem 340 and the intelligent appliance880 are both context-aware (inferred from the user's past/presentactivities, extracted from the user's content/data and explicit in theuser's profile) and sensor-aware (inferred from data/image/patterns fromthe object(s) 720). It should be noted that 5G/higher than 5G bandwidthradio (wireless) transceiver integrated circuit can be fast enough tosecure data from an array of sensors without lag times. The lack of lagtimes can enable a user to physically interact with any remoteenvironment (including haptic sensors). But, full sensory immersionneeded for collaborative telepresence will require lag timessubstantially much smaller than those acceptable for video calls;however a predictive artificial intelligence (PAI) algorithm (stored ina non-transitory media of the intelligent subsystem) can be utilized toeliminate a user's perception of time lags. Thus, the intelligentsubscriber subsystem 340 and/or the intelligent appliance 880 canprovide collaborative telepresence, when the intelligent subscribersubsystem 340 and/or the intelligent appliance 880 is coupled with (orincludes) 5G/higher than 5G bandwidth radio (wireless) transceiver and apredictive artificial intelligence algorithm to eliminate a user'sperception of time lag.

FIG. 11 illustrates a method flow-chart enabling a task execution by asoftware agent. An incoming task is communicated from a communicationchannel 1360, to an incoming queuing element 1380, to an executionmanager 1400. The execution manager 1400 gains information from (andalso shares with) a transient knowledge element 1420 and a data baseelement 1600. The execution manager 1400 further gains information froma permanent knowledge element 1440, which includes an attribute element1460 and a capability element 1480. The capability element 1480 isconnected to a task element 1500, which is further connected to a ruleelement 1520, a method element 1540 and a knowledge source element 1560.Executed/processed tasks from the execution manager 1400, iscommunicated to an outgoing queuing task controller 1580 to thecommunication channel 1360.

Furthermore, the intelligent appliance 880 can be coupled with anaugmented reality apparatus/augmented reality personal assistantapparatus and/or augmented reality application (app).

Additionally, an augmented reality apparatus/augmented reality personalassistant apparatus can include/integrate one or more computationalcamera sensors for three-dimensional viewing and sensing of asurrounding area.

A computational camera sensor can generally include a laser and aphotodiode, wherein the photodiode can be a PIN photodiode, an avalanchephotodiode (APD) or a single photon avalanche detector (SPAD).

Details of the computational camera sensor (e.g., FIGS. 3L-3Z) have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

An augmented reality application can enable a user to share locationbased near real-time/real-time snapshots/holographic snapshots of thecontextual world (or contextual situation) around the user—a way ofviewing the world through someone else's eyes on his/her way to aplace/event.

For example, the user is watching the 2016 NBA final game between theCleveland Cavaliers v. Golden State Warriors, the user (along withhis/her personalized social graph and/or social geotag of geographicaldata (latitude & longitude) with videos, photographs, websites, e-mailsand status updates) may color enhance/edit/geofilter/geotag/personalizethe near real-time/real-time snapshots/holographic snapshots of LebronJames blocking the shot of the Golden State Warriors' Andre Iguodalalike “unbelievable—superman/batman performance by Lebron James” byeither text input or text command in a natural language or voice commandin a natural language from the intelligent appliance 880.

Furthermore, color enhanced/edited/geofiltered/geotagged/personalizedholographic snapshots an individual player can enable a location basedPokémon Go like video game of an individual player.

Details of the augmented reality based application have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/873,634 entitled “SYSTEM AND METHOD FOR MACHINE LEARNING ANDAUGMENTED REALITY BASED USER APPLICATION”, filed on May 26, 2020 and inits related U.S. non-provisional patent applications (with all benefitprovisional patent applications) are incorporated in its entirety hereinwith this application.

Details of the augmented reality device/apparatus have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.16/602,404 entitled “SYSTEM AND METHOD OF AMBIENT/PERVASIVEUSER/HEALTHCARE EXPERIENCE”, filed on Sep. 28, 2019 and in its relatedU.S. non-provisional patent applications (with all benefit provisionalpatent applications) are incorporated in its entirety herein with thisapplication.

Details of the augmented reality personal assistant apparatus have beendescribed/disclosed in U.S. Non-Provisional patent application Ser. No.14/120,835 entitled “AUGMENTED REALITY PERSONAL ASSISTANT APPARATUS”,filed on Jul. 1, 2014, (which resulted in a U.S. Pat. No. 9,823,737,issued on Nov. 21, 2017) and in its related U.S. non-provisional patentapplications (with all benefit provisional patent applications) areincorporated in its entirety herein with this application.

Preferred Embodiments & Scope of the Invention

As used in the above disclosed specifications, the above disclosedspecifications “/” has been used to indicate an “or”.

As used in the above disclosed specifications and in the claims, thesingular forms “a”, “an”, and “the” include also the plural forms,unless the context clearly dictates otherwise.

As used in the above disclosed specifications, the term “includes” means“comprises”. Also the term “including” means “comprising”.

As used in the above disclosed specifications, the term “couples” or“coupled” does not exclude the presence of an intermediate element(s)between the coupled items.

Any dimension in the above disclosed specifications is by way of anapproximation only and not by way of any limitation.

As used in the above disclosed specifications, a hardware module/moduleis defined as an integration of critical electrical/optical/radio/sensorcomponents and circuits (and algorithms, if needed) to achieve a desiredproperty of a hardware module/module.

As used in the above disclosed specifications, a computational camerasensor is generally equivalent to a Light Detection and Ranging (LiDAR)device in meaning and in practice.

As used in the above disclosed specifications, an algorithm is definedas organized set of computer-implementable instructions to achieve adesired task.

As used in the above disclosed specifications, a software module isdefined as a collection of consistent algorithms to achieve a desiredtask.

As used in the above disclosed specifications, real-time means nearreal-time in practice.

Any example in the above disclosed specifications is by way of anexample only and not by way of any limitation. Having described andillustrated the principles of the disclosed technology with reference tothe illustrated embodiments, it will be recognized that the illustratedembodiments can be modified in any arrangement and detail with departingfrom such principles. The technologies from any example can be combinedin any arrangement with the technologies described in any one or more ofthe other examples. Alternatives specifically addressed in thisapplication are merely exemplary and do not constitute all possibleexamples. Claimed invention is disclosed as one of several possibilitiesor as useful separately or in various combinations. See Novozymes A/S v.DuPont Nutrition Biosciences APS, 723 F3d 1336, 1347.

The best mode requirement “requires an inventor(s) to disclose the bestmode contemplated by him/her, as of the time he/she executes theapplication, of carrying out the invention.” “ . . . [T]he existence ofa best mode is a purely subjective matter depending upon what theinventor(s) actually believed at the time the application was filed.”See Bayer AG v. Schein Pharmaceuticals. Inc. The best mode requirementstill exists under the America Invents Act (AIA). At the time of theinvention, the inventor(s) described preferred best mode embodiments ofthe present invention. The sole purpose of the best mode requirement isto restrain the inventor(s) from applying for a patent, while at thesame time concealing from the public preferred embodiments of theirinventions, which they have in fact conceived. The best mode inquiryfocuses on the inventor(s)' state of mind at the time he/she filed thepatent application, raising a subjective factual question. Thespecificity of disclosure required to comply with the best moderequirement must be determined by the knowledge of facts within thepossession of the inventor(s) at the time of filing the patentapplication. See Glaxo. Inc. v. Novopharm Ltd., 52 F.3d 1043, 1050 (Fed.Cir. 1995). The above disclosed specifications are the preferred bestmode embodiments of the present invention. However, they are notintended to be limited only to the preferred best mode embodiments ofthe present invention.

Embodiment by definition is a manner in which an invention can be madeor used or practiced or expressed. “A tangible form or representation ofthe invention” is an embodiment.

Numerous variations and/or modifications are possible within the scopeof the present invention. Accordingly, the disclosed preferred best modeembodiments are to be construed as illustrative only. Those who areskilled in the art can make various variations and/or modificationswithout departing from the scope and spirit of this invention. It shouldbe apparent that features of one embodiment can be combined with one ormore features of another embodiment to form a plurality of embodiments.The inventor(s) of the present invention is not required to describeeach and every conceivable and possible future embodiment in thepreferred best mode embodiments of the present invention. See SRI Int'lv. Matsushita Elec. Corp. of America, 775F.2d 1107, 1121, 227 U.S.P.Q.(BNA) 577, 585 (Fed. Cir. 1985)(enbanc).

The scope and spirit of this invention shall be defined by the claimsand the equivalents of the claims only. The exclusive use of allvariations and/or modifications within the scope of the claims isreserved. The general presumption is that claim terms should beinterpreted using their plain and ordinary meaning without improperlyimporting a limitation from the specification into the claims. SeeContinental Circuits LLC v. Intel Corp. (Appeal Number 2018-1076, Fed.Cir. Feb. 8, 2019) and Oxford Immunotec Ltd. v. Oiagen. Inc. et al.,Action No. 15-cv-13124-NMG. Unless a claim term is specifically definedin the preferred best mode embodiments, then a claim term has anordinary meaning, as understood by a person with an ordinary skill inthe art, at the time of the present invention. Plain claim language willnot be narrowed, unless the inventor(s) of the present invention clearlyand explicitly disclaims broader claim scope. See Sumitomo DainipponPharma Co. v. Emcure Pharm. Ltd., Case Nos. 17-1798; -1799; -1800 (Fed.Cir. Apr. 16, 2018) (Stoll, J). As noted long ago: “Specificationsteach. Claims claim”. See Rexnord Corp. v. Laitram Corp., 274 F.3d 1336,1344 (Fed. Cir. 2001). The rights of claims (and rights of theequivalents of the claims) under the Doctrine of Equivalents-meeting the“Triple Identity Test” (a) performing substantially the same function,(b) in substantially the same way and (c) yielding substantially thesame result. See Crown Packaging Tech., Inc. v. Rexam Beverage Can Co.,559 F.3d 1308, 1312 (Fed. Cir. 2009)) of the present invention are notnarrowed or limited by the selective imports of the specifications (ofthe preferred embodiments of the present invention) into the claims.

While “absolute precision is unattainable” in patented claims, thedefiniteness requirement “mandates clarity.” See Nautilus. Inc. v.Biosig Instruments. Inc., 527 U.S., 134 S. Ct. 2120, 2129, 110 USPQ2d1688, 1693 (2014). Definiteness of claim language must be analyzed NOTin a vacuum, but in light of:

-   -   (a) The content of the particular application disclosure,    -   (b) The teachings of any prior art and    -   (c) The claim interpretation that would be given by one        possessing the ordinary level of skill in the pertinent art at        the time the invention was made. (Id.).        See Orthokinetics. Inc. v. Safety Travel Chairs. Inc., 806 F.2d        1565, 1 USPQ2d 1081 (Fed. Cir. 1986)

There are number of ways the written description requirement issatisfied. Applicant(s) does not need to describe every claim elementexactly, because there is no such requirement (MPEP § 2163). Rather tosatisfy the written description requirement, all that is required is“reasonable clarity” (MPEP § 2163.02). An adequate description may bemade in any way through express, implicit or even inherent disclosuresin the application, including word, structures, figures, diagrams and/orequations (MPEP §§ 2163(I), 2163.02). The set of claims in thisinvention generally covers a set of sufficient number of embodiments toconform to written description and enablement doctrine. See AriadPharm., Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1355 (Fed. Cir. 2010),Regents of the University of California v. Eli Lilly & Co., 119 F.3d1559 (Fed. Cir. 1997) & Amgen Inc. v. Chugai Pharmaceutical Co. 927 F.2d1200 (Fed. Cir. 1991).

Furthermore, Amgen Inc. v. Chugai Pharmaceutical Co. exemplifies'Federal Circuit's strict enablement requirements. Additionally, the setof claims in this invention is intended to inform the scope of thisinvention with “reasonable certainty”. See Interval Licensing, LLC v.AOL Inc. (Fed. Cir. Sep. 10, 2014). A key aspect of the enablementrequirement is that it only requires that others will not have toperform “undue experimentation” to reproduce it. Enablement is notprecluded by the necessity of some experimentation, “[t]he key word is‘undue’, not experimentation.” Enablement is generally considered to bethe most important factor for determining the scope of claim protectionallowed. The scope of enablement must be commensurate with the scope ofthe claims. However, enablement does not require that an inventordisclose every possible embodiment of his invention. The scope of theclaims must be less than or equal to the scope of enablement. SeePromega v. Life Technologies Fed. Cir., December 2014, Magsil v. HitachiGlobal Storage Fed. Cir. August 2012.

The term “means” was not used nor intended nor implied in the disclosedpreferred best mode embodiments of the present invention. Thus, theinventor(s) has not limited the scope of the claims as mean plusfunction.

An apparatus claim with functional language is not an impermissible“hybrid” claim; instead, it is simply an apparatus claim includingfunctional limitations. Additionally, “apparatus claims are notnecessarily indefinite for using functional language . . . [f]unctionallanguage may also be employed to limit the claims without using themeans-plus-function format.” See National Presto Industries. Inc. v. TheWest Bend Co., 76 F. 3d 1185 (Fed. Cir. 1996), R.A.C.C. Indus. v.Stun-Tech. Inc., 178 F.3d 1309 (Fed. Cir. 1998) (unpublished),Miroprocessor Enhancement Corp. v. Texas Instruments Inc. & Williamsonv. Citrix Online, LLC, 792 F.3d 1339 (2015).

I claim:
 1. An intelligent subsystem, wherein the intelligent subsystemis operable with a wireless network or Zigbee, wherein the intelligentsubsystem comprises: (a) a radio transceiver; (b) a microphone; (c) avoice processing module to process a voice command or an audio signal;and wherein the voice processing module comprises one or more firstelectronic components, (d) (i) a microprocessor or (ii) a Super Systemon Chip (SSoC) for fast data processing, image processing/imagerecognition, deep learning/meta-learning or self-learning, wherein theSuper System on Chip (SSoC) comprises (i) a processor-specificelectronic integrated circuit (EIC) and (ii) an array or a network ofmemristors, wherein the intelligent system is communicatively interfacedwith: (i) a first set of computer implementable instructions to processthe voice command or the audio input; wherein the said first set ofcomputer implementable instructions is stored in one or more cloud-basednon-transitory storage media, (ii) a second set of computerimplementable instructions to understand the voice command or the audioinput in a natural language; and wherein the said second set of computerimplementable instructions is stored in the one or more cloud-basednon-transitory storage media, (iii) a third set of computerimplementable instructions to provide learning or intelligence inresponse to a user's interest or a user's preference, that was receivedat the intelligent subsystem, wherein the said third set of computerimplementable instructions comprises artificial intelligence, whereinthe said third set of computer implementable instructions is stored inthe one or more cloud-based non-transitory storage media.
 2. Theintelligent subsystem according to claim 1, is a user-cloud basedsubsystem.
 3. The intelligent subsystem according to claim 1, furthercomprising a camera to identify an object in a field of view, whereinthe camera comprises a digital signal processor (DSP).
 4. Theintelligent subsystem according to claim 3, wherein the camera furthercomprises a metasurface based lens.
 5. The intelligent subsystemaccording to claim 4, wherein the metasurface based lens comprises aphase transition material or a phase change material.
 6. The intelligentsubsystem according to claim 3, wherein the camera further comprises aliquid lens.
 7. The intelligent subsystem according to claim 1, furthercomprising a computational camera sensor for three-dimensional (3-D)sensing of a surrounding area, wherein the computational camera sensorcomprises a laser and a photodiode, wherein the photodiode is selectedfrom the group consisting of the following a PIN photodiode, anavalanche photodiode (APD) and a single photon avalanche detector(SPAD).
 8. The intelligent subsystem according to claim 1, wherein themicroprocessor comprises a neuromorphic visual system, wherein theneuromorphic visual system comprises (i) an array of optically coupledcapacitors or (ii) an array of optically coupled field effecttransistors (FETs).
 9. The intelligent subsystem according to claim 1,further comprising a non-holographic display or a holographic display.10. The intelligent subsystem according to claim 1, further comprisingan electronic module selected from the group consisting of a voiceover-IP module comprising one or more second electronic components, avideo over-IP module comprising one or more third electronic components,a data over-IP module comprising one or more fourth electroniccomponents and a video compression module comprising one or more fifthelectronic components.
 11. The intelligent subsystem according to claim1, wherein the said third set of computer implementable instructionsfurther comprises an artificial neural network.
 12. The intelligentsubsystem according to claim 1, wherein the said third set of computerimplementable instructions further comprises machine learning.
 13. Theintelligent subsystem according to claim 1, wherein the said third setof computer implementable instructions further comprises fuzzy logic.14. The intelligent subsystem according to claim 1, is furthercommunicatively interfaced with a fourth set of computer implementableinstructions to provide a search on an internet in response to theuser's interest or the user's preference, that was received at theintelligent subsystem, wherein the said fourth set of computerimplementable instructions is stored in the one or more cloud-basednon-transitory storage media.
 15. The intelligent subsystem according toclaim 1, is further communicatively interfaced with a fifth set ofcomputer implementable instructions to classify an image, wherein thesaid fifth set of computer implementable instructions is stored in theone or more cloud-based non-transitory storage media.
 16. Theintelligent subsystem according to claim 1, is further communicativelyinterfaced with a sixth set of computer implementable instructions totranslate from a first language to a second language, wherein the saidsixth set of computer implementable instructions is stored in the one ormore cloud-based non-transitory storage media.
 17. An intelligentsubsystem, wherein the intelligent subsystem is operable with a wirelessnetwork or Zigbee, wherein the intelligent subsystem comprises: (a) aradio transceiver; (b) a microphone; (c) a voice processing module toprocess a voice command or an audio signal; and wherein the voiceprocessing module comprises one or more first electronic components, (d)(i) a microprocessor or (ii) a Super System on Chip (SSoC) for fast dataprocessing, image processing/image recognition, deeplearning/meta-learning or self-learning, wherein the Super System onChip (SSoC) comprises (i) a processor-specific electronic integratedcircuit (EIC) and (ii) an array or a network of memristors, wherein theintelligent system is communicatively interfaced with: (i) a first setof computer implementable instructions to process the voice command orthe audio input; wherein the said first set of computer implementableinstructions is stored in one or more cloud-based non-transitory storagemedia, (ii) a second set of computer implementable instructions tounderstand the voice command or the audio input in a natural language;and wherein the said second set of computer implementable instructionsis stored in the one or more cloud-based non-transitory storage media,(iii) a third set of computer implementable instructions to providelearning or intelligence based on a user's interest or a user'spreference, wherein the said third set of computer implementableinstructions comprises artificial intelligence and fuzzy logic, whereinthe said third set of computer implementable instructions is stored inthe one or more cloud-based non-transitory storage media.
 18. Theintelligent subsystem according to claim 17, is a user-cloud basedsubsystem.
 19. The intelligent subsystem according to claim 17, furthercomprising a camera to identify an object in a field of view, whereinthe camera comprises a digital signal processor (DSP).
 20. Theintelligent subsystem according to claim 17, further comprising acomputational camera sensor for three-dimensional (3-D) sensing of asurrounding area, wherein the computational camera sensor comprises alaser and a photodiode, wherein the photodiode is selected from thegroup consisting of the following a PIN photodiode, an avalanchephotodiode (APD) and a single photon avalanche detector (SPAD).
 21. Theintelligent subsystem according to claim 17, wherein the microprocessorcomprises a neuromorphic visual system, wherein the neuromorphic visualsystem comprises (i) an array of optically coupled capacitors or (ii) anarray of optically coupled field effect transistors (FETs).
 22. Theintelligent subsystem according to claim 17, further comprising anon-holographic display or a holographic display.
 23. The intelligentsubsystem according to claim 17, further comprising an electronic moduleselected from the group consisting of a voice over-IP module comprisingone or more second electronic components, a video over-IP modulecomprising one or more third electronic components, a data over-IPmodule comprising one or more fourth electronic components and a videocompression module comprising one or more fifth electronic components.24. The intelligent subsystem according to claim 17, wherein the saidthird set of computer implementable instructions further comprises anartificial neural network.
 25. The intelligent subsystem according toclaim 17, wherein the said third set of computer implementableinstructions further comprises machine learning.
 26. The intelligentsubsystem according to claim 17, is further communicatively interfacedwith a fourth set of computer implementable instructions to provide asearch on an internet based on the user's interest or the user'spreference, wherein the said fourth set of computer implementableinstructions is stored in the one or more cloud-based non-transitorystorage media.
 27. The intelligent subsystem according to claim 17, isfurther communicatively interfaced with a fifth set of computerimplementable instructions to classify an image, wherein the said fifthset of computer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 28. The intelligent subsystemaccording to claim 17, is further communicatively interfaced with asixth set of computer implementable instructions to translate from afirst language to a second language, wherein the said sixth set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 29. An intelligent subsystem,wherein the intelligent subsystem is operable with a wireless network orZigbee, wherein the intelligent subsystem comprises: (a) a radiotransceiver; (b) a microphone; (c) a voice processing module to processa voice command or an audio signal; and wherein the voice processingmodule comprises one or more first electronic components, (d) (i) amicroprocessor or (ii) a Super System on Chip (SSoC) for fast dataprocessing, image processing/image recognition, deeplearning/meta-learning or self-learning, wherein the Super System onChip (SSoC) comprises (i) a processor-specific electronic integratedcircuit (EIC) and (ii) an array or a network of memristors, wherein theintelligent system is communicatively interfaced with: (i) a first setof computer implementable instructions to process the voice command orthe audio input; wherein the said first set of computer implementableinstructions is stored in one or more cloud-based non-transitory storagemedia, (ii) a second set of computer implementable instructions tounderstand the voice command or the audio input in a natural language;wherein the said second set of computer implementable instructions isstored in the one or more cloud-based non-transitory storage media,(iii) a third set of computer implementable instructions to providelearning or intelligence based on a user's interest or a user'spreference; and wherein the said third set of computer implementableinstructions comprises artificial intelligence, wherein artificialintelligence comprises machine learning, wherein the said third set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media, (iv) a fourth set of computerimplementable instructions to provide a search on an internet based onthe user's interest or the user's preference, wherein the said fourthset of computer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 30. The intelligent subsystemaccording to claim 29, is a user-cloud based subsystem.
 31. Theintelligent subsystem according to claim 29, further comprising a camerato identify an object in a field of view, wherein the camera comprises adigital signal processor (DSP).
 32. The intelligent subsystem accordingto claim 29, further comprising a computational camera sensor forthree-dimensional (3-D) sensing of a surrounding area, wherein thecomputational camera sensor comprises a laser and a photodiode, whereinthe photodiode is selected from the group consisting of the following aPIN photodiode, an avalanche photodiode (APD) and a single photonavalanche detector (SPAD).
 33. The intelligent subsystem according toclaim 29, wherein the microprocessor comprises a neuromorphic visualsystem, wherein the neuromorphic visual system comprises (i) an array ofoptically coupled capacitors or (ii) an array of optically coupled fieldeffect transistors (FETs).
 34. The intelligent subsystem according toclaim 29, further comprising a non-holographic display or a holographicdisplay.
 35. The intelligent subsystem according to claim 29, furthercomprising an electronic module selected from the group consisting of avoice over-IP module comprising one or more second electroniccomponents, a video over-IP module comprising one or more thirdelectronic components, a data Over-IP module comprising one or morefourth electronic components and a video compression module comprisingone or more fifth electronic components.
 36. The intelligent subsystemaccording to claim 29, wherein the said third set of computerimplementable instructions further comprises an artificial neuralnetwork.
 37. The intelligent subsystem according to claim 29, whereinthe said third set of computer implementable instructions furthercomprises fuzzy logic.
 38. The intelligent subsystem according to claim29, is further communicatively interfaced with a fifth set of computerimplementable instructions to classify an image, wherein the said fifthset of computer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 39. The intelligent subsystemaccording to claim 29, is further communicatively interfaced with asixth set of computer implementable instructions to translate from afirst language to a second language, wherein the said sixth set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 40. An intelligent subsystem,wherein the intelligent subsystem is operable with a wireless network orZigbee, wherein the intelligent subsystem comprises: (a) a radiotransceiver; (b) a microphone; (c) a voice processing module to processa voice command or an audio signal; and wherein the voice processingmodule comprises one or more first electronic components, (d) (i) amicroprocessor or (ii) a Super System on Chip (SSoC) for fast dataprocessing, image processing/image recognition, deeplearning/meta-learning or self-learning, wherein the Super System onChip (SSoC) comprises (i) a processor-specific electronic integratedcircuit (EIC) and (ii) an array or a network of memristors, wherein theintelligent system is communicatively interfaced with: (i) in a firstset of computer implementable instructions to process the voice commandor the audio input; wherein the said first set of computer implementableinstructions is stored in one or more cloud-based non-transitory storagemedia, (ii) a second set of computer implementable instructions tounderstand the voice command or the audio input in a natural language;and wherein the said second set of computer implementable instructionsis stored in the one or more cloud-based non-transitory storage media,(iii) a third set of computer implementable instructions to providelearning or intelligence based on a user's interest or a user'spreference, wherein the said third set of computer implementableinstructions comprises machine learning, wherein the said third set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 41. The intelligent subsystemaccording to claim 40, is a user-cloud based subsystem.
 42. Theintelligent subsystem according to claim 40, further comprising acomputational camera sensor for three-dimensional (3-D) sensing of asurrounding area, wherein the computational camera sensor comprises alaser and a photodiode, wherein the photodiode is selected from thegroup consisting of the following a PIN photodiode, an avalanchephotodiode (APD) and a single photon avalanche detector (SPAD).
 43. Theintelligent subsystem according to claim 40, further comprising anelectronic module selected from the group consisting of a voice over-IPmodule comprising one or more second electronic components, a videoover-IP module comprising one or more third electronic components, adata over-IP module comprising one or more fourth electronic componentsand a video compression module comprising one or more fifth electroniccomponents.
 44. The intelligent subsystem according to claim 40, whereinthe said third set of computer implementable instructions furthercomprises an artificial neural network.
 45. The intelligent subsystemaccording to claim 40, wherein the said third set of computerimplementable instructions further comprises fuzzy logic.
 46. Theintelligent subsystem according to claim 40, is further communicativelyinterfaced with a fourth set of computer implementable instructions toprovide a search on an internet based on the user's interest or theuser's preference, wherein the said fourth set of computer implementableinstructions is stored in the one or more cloud-based non-transitorystorage media.
 47. The intelligent subsystem according to claim 40, isfurther communicatively interfaced with a fifth set of computerimplementable instructions to classify an image, wherein the said fifthset of computer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 48. The intelligent subsystemaccording to claim 40, is further communicatively interfaced with asixth set of computer implementable instructions to translate from afirst language to a second language, wherein the said sixth set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 49. An intelligent subsystem,wherein the intelligent subsystem is operable with a wireless network orZigbee, wherein the intelligent subsystem a user-cloud based subsystem,wherein the intelligent subsystem comprises: (a) a radio transceiver;(b) a microphone; (c) a voice processing module to process a voicecommand or an audio signal; and wherein the voice processing modulecomprises one or more first electronic components, (d) (i) amicroprocessor or (ii) a Super System on Chip (SSoC) for fast dataprocessing, image processing/image recognition, deeplearning/meta-learning or self-learning, wherein the Super System onChip (SSoC) comprises (i) a processor-specific electronic integratedcircuit (EIC) and (ii) an array or a network of memristors, wherein theintelligent system is communicatively interfaced with: (i), a first setof computer implementable instructions to process the voice command orthe audio input; wherein the said first set of computer implementableinstructions is stored in one or more cloud-based non-transitory storagemedia, (ii) a second set of computer implementable instructions tounderstand the voice command or the audio input in a natural language;and wherein the said second set of computer implementable instructionsis stored in the one or more cloud-based non-transitory storage media,(iii) a third set of computer implementable instructions to providelearning or intelligence based on a user's interest or a user'spreference, wherein the said third set of computer implementableinstructions comprises an artificial neural network, wherein the saidthird set of computer implementable instructions is stored in the one ormore cloud-based non-transitory storage media.
 50. The intelligentsubsystem according to claim 49, further comprising an electronic moduleselected from the group consisting of a voice over-IP module comprisingone or more second electronic components, a video over-IP modulecomprising one or more third electronic components, a data over-IPmodule comprising one or more fourth electronic components and a videocompression module comprising one or more fifth electronic components.51. The intelligent subsystem according to claim 49, wherein the saidthird set of computer implementable instructions further comprisesmachine learning.
 52. The intelligent subsystem according to claim 49,wherein the said third set of computer implementable instructionsfurther comprises fuzzy logic.
 53. The intelligent subsystem accordingto claim 49, is further communicatively interfaced with a fourth set ofcomputer implementable instructions to provide a search on an internetbased on the user's interest or the user's preference, wherein the saidfourth set of computer implementable instructions is stored in the oneor more cloud-based non-transitory storage media.
 54. An intelligentsubsystem, wherein the intelligent subsystem is operable with a wirelessnetwork, wherein the intelligent subsystem comprises: (a) a radiotransceiver; (b) a microphone; (c) a voice processing module to processan audio signal; and wherein the voice processing module comprises oneor more first electronic components, (d) a Super System on Chip (SSoC)for fast data processing, image processing/image recognition, deeplearning/meta-learning or self-learning, wherein the Super System onChip (SSoC) comprises (i) a processor-specific electronic integratedcircuit (EIC) and (ii) memristors, wherein the intelligent system iscommunicatively interfaced with: (i) a first set of computerimplementable instructions to process the audio signal; wherein the saidfirst set of computer implementable instructions is stored in one ormore cloud-based non-transitory storage media, (ii) a second set ofcomputer implementable instructions to understand the audio signal in anatural language; wherein the said second set of computer implementableinstructions is stored in the one or more cloud-based non-transitorystorage media, (iii) a third set of computer implementable instructionsto provide learning or intelligence in response to a user's interest, ora user's preference, that was received at the intelligent subsystem; andwherein the said third set of computer implementable instructionscomprises artificial intelligence, wherein artificial intelligencecomprises machine learning, wherein the said third set of computerimplementable instructions is stored in the one or more cloud-basednon-transitory storage media, (iv) a fourth set of computerimplementable instructions to provide a search on an internet inresponse to the user's interest or the user's preference, that wasreceived at the intelligent subsystem, wherein the said fourth set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 55. The intelligent subsystemaccording to claim 54, is a user-cloud based subsystem.
 56. Theintelligent subsystem according to claim 54, is a cloud based subsystem.57. The intelligent subsystem according to claim 54, wherein the audiosignal comprises a voice command.
 58. The intelligent subsystemaccording to claim 54, wherein the said third set of computerimplementable instructions further comprises fuzzy logic.
 59. Theintelligent subsystem according to claim 54, further comprising adisplay.
 60. An intelligent subsystem, wherein the intelligent subsystemis operable with a wireless network, wherein the intelligent subsystemcomprises: (a) a radio transceiver; (b) a microphone; (c) a voiceprocessing module to process an audio signal; and wherein the voiceprocessing module comprises one or more first electronic components, (d)a Super System on Chip (SSoC) for fast data processing, imageprocessing/image recognition, deep learning/meta-learning orself-learning, wherein the Super System on Chip (SSoC) comprises (i) aprocessor-specific electronic integrated circuit (EIC) and (ii)memristors, wherein the intelligent system is communicatively interfacedwith: (i) a first set of computer implementable instructions to processthe audio signal; wherein the said first set of computer implementableinstructions is stored in one or more cloud-based non-transitory storagemedia, (ii) a second set of computer implementable instructions tounderstand the audio signal in a natural language; wherein the saidsecond set of computer implementable instructions is stored in the oneor more cloud-based non-transitory storage media, (iii) a third set ofcomputer implementable instructions to provide learning or intelligencein response to a user's interest, or a user's preference, that wasreceived at the intelligent subsystem; and wherein the said third set ofcomputer implementable instructions comprises artificial intelligence,wherein artificial intelligence comprises machine learning, wherein thesaid third set of computer implementable instructions is stored in theone or more cloud-based non-transitory storage media, (iv) a fourth setof computer implementable instructions to provide an automatic search onan internet in response to the user's interest or the user's preference,that was received at the intelligent subsystem, wherein the said fourthset of computer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 61. The intelligent subsystemaccording to claim 60, is a user-cloud based subsystem.
 62. Theintelligent subsystem according to claim 60, is a cloud based subsystem.63. The intelligent subsystem according to claim 60, wherein the audiosignal comprises a voice command.
 64. The intelligent subsystemaccording to claim 60, wherein the said third set of computerimplementable instructions further comprises fuzzy logic.
 65. Theintelligent subsystem according to claim 60, further comprising adisplay.
 66. An intelligent subsystem, wherein the intelligent subsystemis operable with a wireless network, wherein the intelligent subsystemcomprises: (a) a radio transceiver; (b) a microphone; (c) a voiceprocessing module to process an audio signal; and wherein the voiceprocessing module comprises one or more first electronic components, (d)a microprocessor, wherein the intelligent system is communicativelyinterfaced with: (i) a first set of computer implementable instructionsto process the audio signal; wherein the said first set of computerimplementable instructions is stored in one or more cloud-basednon-transitory storage media, (ii) a second set of computerimplementable instructions to understand the audio signal in a naturallanguage; wherein the said second set of computer implementableinstructions is stored in the one or more cloud-based non-transitorystorage media, (iii) a third set of computer implementable instructionsto provide learning or intelligence in response to a user's interest, ora user's preference, that was received at the intelligent subsystem; andwherein the said third set of computer implementable instructionscomprises artificial intelligence, wherein artificial intelligencecomprises an artificial neural network, wherein the said third set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media, (iv) a fourth set of computerimplementable instructions to provide a search on an internet inresponse to the user's interest, or the user's preference, that wasreceived at the intelligent subsystem, wherein the said fourth set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 67. The intelligent subsystemaccording to claim 66, is a user-cloud based subsystem.
 68. Theintelligent subsystem according to claim 66, is a cloud based subsystem.69. The intelligent subsystem according to claim 66, wherein the audiosignal comprises a voice command.
 70. The intelligent subsystemaccording to claim 66, further comprising a display.
 71. An intelligentsubsystem, wherein the intelligent subsystem is operable with a wirelessnetwork, wherein the intelligent subsystem comprises: (a) a radiotransceiver; (b) a microphone; (c) a voice processing module to processan audio signal; and wherein the voice processing module comprises oneor more first electronic components, (d) a microprocessor, wherein theintelligent system is communicatively interfaced with: (i) a first setof computer implementable instructions to process the audio signal;wherein the said first set of computer implementable instructions isstored in one or more cloud-based non-transitory storage media, (ii) asecond set of computer implementable instructions to understand theaudio signal in a natural language; wherein the said second set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media, (iii) a third set of computerimplementable instructions to provide learning or intelligence inresponse to a user's interest, or a user's preference, that was receivedat the intelligent subsystem; and wherein the said third set of computerimplementable instructions comprises artificial intelligence, whereinartificial intelligence comprises an artificial neural network, whereinthe said third set of computer implementable instructions is stored inthe one or more cloud-based non-transitory storage media, (iv) a fourthset of computer implementable instructions to provide an automaticsearch on an internet in response to the user's interest, or the user'spreference, that was received at the intelligent subsystem, wherein thesaid fourth set of computer implementable instructions is stored in theone or more cloud-based non-transitory storage media.
 72. Theintelligent subsystem according to claim 71, is a user-cloud basedsubsystem.
 73. The intelligent subsystem according to claim 71, is acloud based subsystem.
 74. The intelligent subsystem according to claim71, wherein the audio signal comprises a voice command.
 75. Theintelligent subsystem according to claim 71, further comprising adisplay.
 76. An intelligent subsystem, wherein the intelligent subsystemis operable with a wireless network, wherein the intelligent subsystemcomprises: (a) a radio transceiver; (b) a microphone; (c) a voiceprocessing module to process an audio signal; and wherein the voiceprocessing module comprises one or more first electronic components, (d)a microprocessor, wherein the intelligent system is communicativelyinterfaced with: (i) a first set of computer implementable instructionsto process the audio signal; wherein the said first set of computerimplementable instructions is stored in one or more cloud-basednon-transitory storage media, (ii) a second set of computerimplementable instructions to understand the audio signal in a naturallanguage; wherein the said second set of computer implementableinstructions is stored in the one or more cloud-based non-transitorystorage media, (iii) a third set of computer implementable instructionsto provide learning or intelligence in response to a user's interest, ora user's preference, that was received at the intelligent subsystem; andwherein the said third set of computer implementable instructionscomprises artificial intelligence and fuzzy logic, wherein the saidthird set of computer implementable instructions is stored in the one ormore cloud-based non-transitory storage media, (iv) a fourth set ofcomputer implementable instructions to provide a search on an internetin response to the user's interest, or the user's preference, that wasreceived at the intelligent subsystem, wherein the said fourth set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media.
 77. An intelligent subsystem,wherein the intelligent subsystem is operable with a wireless network,wherein the intelligent subsystem comprises: (a) a radio transceiver;(b) a microphone; (c) a voice processing module to process an audiosignal; and wherein the voice processing module comprises one or morefirst electronic components, (d) a microprocessor, wherein theintelligent system is communicatively interfaced with: (i) a first setof computer implementable instructions to process the audio signal;wherein the said first set of computer implementable instructions isstored in one or more cloud-based non-transitory storage media, (ii) asecond set of computer implementable instructions to understand theaudio signal in a natural language; wherein the said second set ofcomputer implementable instructions is stored in the one or morecloud-based non-transitory storage media, (iii) a third set of computerimplementable instructions to provide learning or intelligence inresponse to a user's interest, or a user's preference, that was receivedat the intelligent subsystem; and wherein the said third set of computerimplementable instructions comprises artificial intelligence and fuzzylogic, wherein the said third set of computer implementable instructionsis stored in the one or more cloud-based non-transitory storage media,(iv) a fourth set of computer implementable instructions to provide anautomatic search on an internet in response to the user's interest, orthe user's preference, that was received at the intelligent subsystem,wherein the said fourth set of computer implementable instructions isstored in the one or more cloud-based non-transitory storage media.